Searching method and device applied to hearing aid, hearing aid, medium and product

Abstract

The invention discloses a searching method and device applied to a hearing aid, the hearing aid, a medium and a product, and relates to the technical field of hearing aids, and the searching method comprises the steps: obtaining the use data of each electronic device, the use data comprising the use frequency, the use duration and the use function; performing prediction through a prediction model based on the use data to obtain target electronic equipment; when it is judged that the hearing aid is lost, a positioning signal at the loss moment is sent to the target electronic equipment, and the target electronic equipment is used for prompting a loss place of the hearing aid at the loss moment. According to the invention, through the intelligent prediction and positioning technology, in combination with the cooperative work of multiple devices, and through the behavior of searching the hearing aid through linkage with the target electronic device, searching can be carried out without depending on a Bluetooth signal, and the user can be informed of the loss place of the hearing aid at the loss moment in time, so that the recovery efficiency can be improved, and the searching difficulty can be reduced.

Description

Technical Field

[0001] The present application relates to the technical field of hearing aids, and in particular to a search method for hearing aids, a search device for hearing aids, a hearing aid, a storage medium and a computer program product. Background Art

[0002] For users who rely on hearing aids, once they lose their hearing aids, hearing impairments may make it difficult for them to locate them through sound clues, such as not being able to hear the faint sound of a drop or finding the source of a faint battery sound. Currently, although hearing aids are integrated with Bluetooth tracking functions, when the hearing aid battery is exhausted, it will shut down and turn off the Bluetooth function, making it difficult to search for a lost hearing aid. Summary of the invention

[0003] The main purpose of the present application is to provide a search method for hearing aids, a search device for hearing aids, a hearing aid, a storage medium and a computer program product, aiming to solve the technical problem of high difficulty in searching for lost hearing aids.

[0004] To achieve the above objectives, the present application proposes a search method for hearing aids, the search method for hearing aids comprising:

[0005] Acquire usage data of each electronic device, wherein the usage data includes usage frequency, usage duration, and usage function;

[0006] Perform prediction based on the usage data using a prediction model to obtain a target electronic device;

[0007] When it is determined that the hearing aid is lost, a positioning signal of the time of loss is sent to the target electronic device, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

[0008] In one embodiment, before the step of predicting based on the usage data by using a prediction model to obtain a target electronic device, the step includes:

[0009] Acquire historical usage data of each electronic device and a corresponding historical target electronic device, wherein the historical usage data includes historical usage frequency, historical usage duration, and historical usage function;

[0010] The historical usage data and the historical target electronic devices are trained to obtain a prediction model for screening target electronic devices.

[0011] In one embodiment, the method for determining a target electronic device further includes:

[0012] Scoring each electronic device according to a preset rule to obtain a scoring result, wherein the attributes measured by the preset rule include the usage time, online time, preset usage probability, signal penetration capability and signal strength of each electronic device;

[0013] The target electronic device is screened based on the scoring result.

[0014] In one embodiment, before the step of obtaining the scoring result, the following steps are included:

[0015] Recording interaction data with each electronic device, wherein the interaction data includes the amount of interaction data and the number of connections;

[0016] The degree of dependence on each electronic device is determined according to the interaction data, and the scoring weight of the preset rule is adjusted according to the degree of dependence.

[0017] In one embodiment, the types of interaction data include direct interaction data and indirect interaction data, and the step of recording the interaction data with each electronic device includes:

[0018] If the interaction with each electronic device is carried out through a wireless connection, the data generated is direct interaction data;

[0019] If the user interacts with each electronic device through voice commands, the data generated is indirect interaction data.

[0020] In one embodiment, the search method applied to a hearing aid further includes:

[0021] Determine whether you are outdoors based on location data;

[0022] If the device is outdoors and is determined to be lost, the historical loss data and historical behavior data at the time of loss are obtained;

[0023] By presetting the neural network model, the probability of loss under the preset behavior is obtained;

[0024] When a preset behavior is detected, a reminder will be lost.

[0025] In addition, to achieve the above-mentioned purpose, the present application also proposes a search device applied to a hearing aid, the search device applied to a hearing aid comprising: an acquisition module, used to acquire usage data of each electronic device, wherein the usage data includes usage frequency, usage duration and usage function;

[0026] A prediction module, configured to make a prediction based on the usage data by using a prediction model to obtain a target electronic device;

[0027] The search module is used to send a positioning signal of the time of loss to the target electronic device when the hearing aid is determined to be lost, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

[0028] In addition, to achieve the above objectives, the present application also proposes a hearing aid, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the search method applied to the hearing aid as described above.

[0029] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the search method applied to the hearing aid as described above are implemented.

[0030] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the search method applied to the hearing aid as described above are implemented.

[0031] After acquiring the usage data of each electronic device, the present application performs prediction through a prediction model to obtain a target electronic device. When the hearing aid is determined to be lost, a positioning signal of the time of loss is sent to the target electronic device, and the target electronic device prompts the location where the hearing aid was lost at the time of loss.

[0032] Compared with the existing technology of searching through Bluetooth tracking technology, when the battery is exhausted, the Bluetooth signal cannot be sent, making the search difficult; through intelligent prediction and positioning technology, combined with the collaborative work of multiple devices, the behavior of searching for hearing aids is linked with the target electronic device. It is possible to search without relying on Bluetooth signals, and the user can be notified in time of the lost location of the hearing aid at the time of loss, which helps to improve the recovery efficiency and reduce the difficulty of searching. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1A flowchart of a first embodiment of the search method for hearing aids provided by the present application;

[0036] Figure 2 A flowchart diagram of a second embodiment of the search method for hearing aids provided by the present application;

[0037] Figure 3 This is a schematic diagram of the module structure of the search device for hearing aids used in the present application;

[0038] Figure 4 This is a schematic diagram of the device structure of the hardware operating environment involved in the hearing aid search method of the present application.

[0039] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0040] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0041] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0042] Since only the Bluetooth tracking function of the hearing aid itself is used, it is difficult to search through the Bluetooth signal when the hearing aid is lost; and the hearing impairment of the user itself will make the hearing aid itself used for lost reminders often ineffective when the hearing aid is lost. Using the target electronic device as a temporary reminder device will not be limited by the user's hearing limitations, nor will it be limited by the hearing aid battery being exhausted, resulting in the inability to use the Bluetooth tracking function.

[0043] Therefore, this application obtains the usage data of each electronic device in the room through the hearing aid, and uses a prediction model to predict the electronic devices commonly used by the user (i.e., the target electronic devices). When the hearing aid is lost, the location where the hearing aid is lost is reminded through the commonly used devices, making it easier for the user to search for the hearing aid.

[0044] It should be noted that the execution subject of this embodiment may be a hearing aid, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a processor, etc. capable of realizing the above functions. The following takes a hearing aid as an example to illustrate this embodiment and the following embodiments.

[0045] Based on this, the embodiment of the present application provides a search method for a hearing aid, which is applied to a hearing aid, referring to Figure 1 , Figure 1FIG. 1 is a flow chart of a first embodiment of a search method for hearing aids according to the present application.

[0046] In some embodiments, the hearing aid may be a RIC (Receiver-In-Canal) type hearing aid.

[0047] In this embodiment, the search method for hearing aids includes steps S10 to S30:

[0048] Step S10, obtaining usage data of each electronic device, wherein the usage data includes usage frequency, usage duration and usage function;

[0049] It should be noted that hearing aids obtain usage data of electronic devices through various sensors. Usage data is data generated when users operate electronic devices, including frequency of use, duration of use, and functions used. These data can reflect the user's interaction patterns and preferences with the device.

[0050] Specifically, the frequency of use refers to the number of times a user uses an electronic device per unit time. For example, the number of times a refrigerator is opened in a day, or the number of times it is used in a week. The duration of use refers to the duration of each time a user uses an electronic device, which can be a single time or the cumulative time within a certain period. For example, the length of time a user turns on the air conditioner every day, or the total time the air conditioner is used continuously. The usage function refers to the specific usage function on the electronic device. For example, a microwave oven can make a loud and penetrating "ding" sound, the TV can cast the screen, and the voice assistant (such as Xiao Ai and Xiaodu) can perform vibration reminders, text floating screens, etc.

[0051] Step S20, performing prediction based on the usage data through a prediction model to obtain a target electronic device;

[0052] It should be noted that the prediction model is based on the usage data of electronic devices. Through algorithm analysis and learning, it can predict and identify electronic devices; the target electronic device has the function of prompting the location where the hearing aid is lost, including but not limited to flash screen reminders, vibration reminders, voice reminders... For example, the target electronic device can be a refrigerator, microwave oven, air conditioner, voice assistant, etc.

[0053] In a feasible implementation manner, before step S20, steps A10 to A20 are included:

[0054] Step A10, acquiring historical usage data of each electronic device and a corresponding historical target electronic device, wherein the historical usage data includes historical usage frequency, historical usage duration, and historical usage function;

[0055] It should be noted that in order to train the prediction model, it is necessary to obtain the historical usage data of each electronic device within a certain time range (such as one month, one week), and the historical usage data includes historical usage frequency, historical usage duration and historical usage functions; among which, the historical target electronic device can be one or more electronic devices specified by the user that generate the historical usage data.

[0056] Step A20: training the historical usage data and the historical target electronic devices to obtain a prediction model for screening target electronic devices.

[0057] It should be noted that the prediction model can predict which devices are more likely to become target electronic devices in future usage scenarios by learning the association between historical usage data and historical target electronic devices. The target electronic devices are more closely associated with the user and have a high probability of being used by the user, which can be used conveniently and accurately to remind the user of the lost location of the hearing aid.

[0058] In one embodiment, the training process generally involves dividing the data set into a training set and a test set, so that the model can learn patterns using the training set and verify its performance using the test set. By using the historical usage data and the historical target electronic devices as inputs for model training, the prediction model trained thereby can screen the target electronic devices.

[0059] It is understandable that through machine learning and data analysis, an intelligent and efficient device usage experience can be achieved.

[0060] In this embodiment, the prediction model can quickly filter out the target device from a large number of devices, thereby improving the efficiency of the screening process; based on historical data and model predictions, the target device can be selected more quickly and intuitively, so that the target device can provide efficient reminders when the hearing aid is lost, helping the user to retrieve the lost hearing aid more quickly.

[0061] Step S30, when it is determined that the hearing aid is lost, a positioning signal of the time of loss is sent to the target electronic device, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

[0062] It should be noted that the hearing aid can be determined to be lost in the following ways: when the built-in motion sensor of the hearing aid detects an abnormal state (such as being still for a long time or moving suddenly), it can be determined that the hearing aid may be lost; or when the communication status between the hearing aid and another electronic device is monitored, when the hearing aid is disconnected for more than a certain period of time, it can be determined that the hearing aid may be lost. The moment of loss refers to the moment when the hearing aid is determined to be lost, which is a point in time; when it is determined to be lost, the hearing aid will send a positioning signal of the moment of loss to the target electronic device. Once the location where the hearing aid is lost is determined, the target electronic device will prompt the user in various ways, including but not limited to visual prompts (such as displaying a location map of the hearing aid on a smartphone), sound prompts (such as a smart speaker playing a specific sound or information to indicate the location of the hearing aid), and vibration prompts (if the target device supports vibration, such as a smart watch or mobile phone, it can prompt the user through vibration).

[0063] In this embodiment, after obtaining the usage data of each electronic device, the usage data is analyzed using a predictive model to identify the target electronic device; when the hearing aid is lost, the user's other electronic devices can be used to provide location information in an indirect way, even if the hearing aid is lost or cannot be directly located, to help the user quickly find the hearing aid and reduce the inconvenience and loss caused by the loss.

[0064] In another feasible implementation, the search method for hearing aids further includes steps B10 to B40:

[0065] Step B10, determining whether the user is outdoors according to the location data;

[0066] It should be noted that the hearing aid obtains location data through the positioning sensor and determines whether the user is outdoors based on the location data. Since the hearing aid may be lost outdoors, the hearing aid is designed to collect location data.

[0067] Step B20, if the device is outdoors and is determined to be lost, obtaining historical loss data and historical behavior data when the device was lost;

[0068] It should be noted that outdoor means that the hearing aid is lost in an outdoor space; historical loss data refers to detailed records of past device loss events, including but not limited to the location, time, and method of recovery. Historical behavior data at the time of loss is a record of the user's activities in the period before the hearing aid was lost. This data may include the user's movement trajectory, visited places, activities performed, etc. By analyzing these historical behavior data, it is possible to infer the user's possible behavior when the loss occurred.

[0069] It is understandable that by analyzing historical loss data, high-incidence areas of hearing aid loss can be identified; combined with historical behavioral data at the time of loss, the user's behavior and the time of occurrence when the hearing aid was lost can be obtained, such as: taking a walk at 8 o'clock, running at 10 o'clock, sitting still at 14 o'clock, etc.

[0070] Step B30, obtaining the probability of loss under the preset behavior by presetting the neural network model;

[0071] It should be noted that the historical loss data and the historical behavior data at the time of loss are obtained through a preset neural network model to obtain the probability of hearing aid loss under different behaviors. For example, the probability of loss in running state is 80%, the probability of loss in walking state is 40%, and the probability of loss in sitting state is 5%.

[0072] The process of calculating the loss probability through a preset neural network model includes: extracting key features from the preset behavior, using the trained model, inputting feature data, and the model will output a probability value, indicating the possibility of device loss under the preset behavior. Based on the output probability value, the level of loss risk can be evaluated, and then corresponding preventive measures can be taken.

[0073] Step B40, when the preset behavior is detected, a loss reminder is issued.

[0074] It should be noted that when running behavior is detected, the user is reminded that loss will occur, allowing the user to take preventive measures in advance.

[0075] In this embodiment, the neural network-based prediction method can provide users with real-time risk warnings, helping users take measures to reduce the possibility of hearing aid loss. Through continuous learning and optimization, the preset neural network model can continuously improve its prediction accuracy and provide accurate data for hearing aid management.

[0076] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can refer to the above introduction, and will not be repeated in the following. Figure 2 The method for determining the target electronic device further includes steps D10 to D20:

[0077] Step D10, scoring each electronic device according to preset rules to obtain a scoring result, wherein the preset rules include usage time, online time, preset usage probability, signal penetration capability and signal strength of each electronic device;

[0078] It should be noted that the preset rules are used to measure specific attributes of electronic devices, including usage time, online time, preset usage probability, signal penetration ability and signal strength; usage time refers to the actual usage time, reflecting the activity of the device; online time refers to the time the device remains connected to the network, reflecting the availability and stability of the device; preset usage probability refers to the probability of user use within a week or a month, such as the probability of refrigerator use is 100%, the probability of microwave oven use is 30%, etc., to screen users' commonly used electronic devices. Signal penetration ability The ability of device signals to penetrate obstacles (such as walls) reflects the performance of the device in complex environments. For example, when reminding the hearing aid where it is lost, the stronger the sound signal penetration ability, the greater the chance of being noticed by the user. Signal strength refers to the strength of the positioning signal sent by the hearing aid.

[0079] The specific rules for scoring include quantifying these rules, such as using time in hours, online time in days, and signal strength in dBm (decibel milliwatt, a unit of measurement), and then calculating the total score of each device or the sub-score of each performance based on these quantified values. For example: the usage time is A, the weight is α; the online time is B, the weight is β; the preset usage probability is C, the weight is γ; the signal penetration ability is E, the weight is δ; the signal strength is F, the weight is θ; the final score result is S, which is calculated by the following formula.

[0080]

[0081] The scoring result is a numerical value or grade obtained by evaluating each electronic device based on all the above rules. These results can be used to compare the performance of different devices and provide data support for reminding the lost hearing aid location.

[0082] In a feasible implementation manner, before step D10, steps E10 to E20 are included:

[0083] Step E10, recording interaction data with each electronic device, wherein the interaction data includes interaction data volume and connection times;

[0084] It should be noted that interaction data refers to the data generated during the interaction between the electronic device and the hearing aid, such as wireless connection; the interaction data volume is the amount of interactive data per unit time; the number of connections is the number of times the hearing aid successfully establishes a connection with the electronic device.

[0085] In another feasible implementation, step E10 includes steps T10 to T20:

[0086] Step T10, if the interaction with each electronic device is performed via a wireless connection, the generated data is direct interaction data;

[0087] It should be noted that wireless connection refers to the interaction between the hearing aid and various electronic devices through wireless networks (such as Wi-Fi, Bluetooth, cellular networks, etc.); in the wireless connection scenario, each interaction between the hearing aid and each electronic device will generate data, and this data generated by wireless interaction is called direct interaction data.

[0088] Step T20: If the user interacts with each electronic device through voice commands, the generated data is indirect interaction data.

[0089] It should be noted that voice commands are a form of interaction where users interact with electronic devices through voice (e.g., please connect a hearing aid to a smart player). When users interact with electronic devices through voice commands, the data generated is defined as indirect interaction data. “Indirect” means that users do not interact with devices directly through physical operations, but through the medium of voice.

[0090] In this embodiment,

[0091] Step E20, determining the degree of dependence on each electronic device according to the interaction data, and adjusting the scoring weight of the preset rule according to the degree of dependence.

[0092] It should be noted that the degree of dependence of the hearing aid on the electronic device is determined based on the interaction data of the device, which is used to measure the importance of the electronic device to the user, so that electronic devices with high importance can be used as auxiliary devices for searching for hearing aids.

[0093] The specific steps of "determination" are: first, statistics are collected on the interaction data, such as mean, median, standard deviation, etc., to quantify the usage of the device; then, weights are assigned according to the importance of the indicators, such as data transmission volume may have a higher weight than the number of connections; finally, the dependency is scored using methods such as Z-score standardization or percentile ranking.

[0094] The weight in the scoring rule is the importance coefficient of each evaluation indicator, which determines the influence of each indicator when scoring. By analyzing the degree of dependence, these weights can be adjusted to make the scoring results more in line with actual needs and the true value of the equipment. For example: If it is found that the amount of interaction data and the number of connections between an electronic device and a hearing aid far exceed other devices, this indicates that the electronic device is a key electronic device, then the weight of indicators related to the interaction data, such as "usage time" and "online time", can be increased accordingly. On the contrary, if the degree of dependence of a certain device is low, the weight of its related indicators can be appropriately reduced to avoid giving it an over-rating in the scoring.

[0095] In this embodiment, by dynamically adjusting the scoring weight mechanism, it is possible to ensure that the scoring results more objectively and accurately reflect the actual degree of user dependence on each electronic device, and provide data support for selecting a suitable hearing aid. This not only enhances the flexibility and adaptability of the scoring system, but also improves the accuracy of the selection, which helps to more efficiently find the lost hearing aid.

[0096] Step D20: Screening and obtaining target electronic devices based on the scoring results.

[0097] It should be noted that the scoring results serve as a basis for evaluating whether a device can be used as a reminder device. Based on the scoring results, electronic devices with the highest scores are selected, and these electronic devices are considered to be the best electronic devices to be used as reminder devices.

[0098] In this embodiment, a comprehensive and objective evaluation of electronic devices can be achieved through a scoring mechanism, allowing users to make judgments based on the data and use it as a reminder device to search for hearing aids; screening based on the scoring results helps ensure that appropriate electronic devices are selected, thereby improving the success rate of the search and reducing the difficulty of the search.

[0099] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the search method of the present application for hearing aids. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0100] This application also provides a search device for hearing aids, please refer to Figure 3 , the search device applied to the hearing aid comprises:

[0101] The acquisition module 10 is used to acquire the usage data of each electronic device, wherein the usage data includes the usage frequency, usage duration and usage function;

[0102] A prediction module 20, configured to perform prediction based on the usage data through a prediction model to obtain a target electronic device;

[0103] The search module 30 is used to send a positioning signal of the time of loss to the target electronic device when the hearing aid is determined to be lost, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

[0104] Optionally, the prediction module 20 is further used to obtain historical usage data of each electronic device and a corresponding historical target electronic device, wherein the historical usage data includes historical usage frequency, historical usage duration, and historical usage function;

[0105] The historical usage data and the historical target electronic devices are trained to obtain a prediction model for screening target electronic devices.

[0106] Optionally, the prediction module 20 is further used to score the electronic devices according to preset rules to obtain a scoring result, wherein the attributes measured by the preset rules include the usage time, online time, preset usage probability, signal penetration capability and signal strength of each electronic device;

[0107] The target electronic device is screened based on the scoring result.

[0108] Optionally, the prediction module 20 is further used to record interaction data with each electronic device, wherein the interaction data includes the amount of interaction data and the number of connections;

[0109] The degree of dependence on each electronic device is determined according to the interaction data, and the scoring weight of the preset rule is adjusted according to the degree of dependence.

[0110] Optionally, the prediction module 20 is further configured to generate direct interaction data if the interaction is performed with each electronic device via a wireless connection;

[0111] If the user interacts with each electronic device through voice commands, the data generated is indirect interaction data.

[0112] The search device for hearing aids further comprises: determining whether the device is outdoors according to the location data;

[0113] If the device is outdoors and is determined to be lost, the historical loss data and historical behavior data at the time of loss are obtained;

[0114] By presetting the neural network model, the probability of loss under the preset behavior is obtained;

[0115] When a preset behavior is detected, a reminder will be lost.

[0116] The search device for hearing aids provided by the present application adopts the search method for hearing aids in the above embodiment, which can solve the technical problem of high difficulty in searching for hearing aids. Compared with the prior art, the beneficial effects of the search device for hearing aids provided by the present application are the same as the beneficial effects of the search method for hearing aids provided by the above embodiment, and other technical features of the search device for hearing aids are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0117] In one embodiment, the search device applied to the hearing aid can be the hearing aid itself, or it can be other devices that can be used to search for hearing aids, integrated in the hearing aid, including but not limited to Bluetooth trackers, radio frequency identification trackers and GPS (Global Positioning System) tracking devices.

[0118] The present application provides a hearing aid, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the search method applied to the hearing aid in the first embodiment described above.

[0119] Reference below Figure 4 , which shows a schematic diagram of the structure of a hearing aid suitable for implementing the embodiment of the present application. The hearing aid in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The hearing aid shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0120] like Figure 4 As shown, the hearing aid may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for the operation of the hearing aid are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the hearing aid to communicate with other devices wirelessly or by wire to exchange data. Although the figures show hearing aids with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0121] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0122] The hearing aid provided by the present application adopts the search method applied to the hearing aid in the above embodiment, which can solve the technical problem of high difficulty in searching for lost hearing aids. Compared with the prior art, the beneficial effects of the hearing aid provided by the present application are the same as the beneficial effects of the search method applied to the hearing aid provided in the above embodiment, and other technical features in the hearing aid are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0123] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0124] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0125] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the search method applied to the hearing aid in the above-mentioned embodiment.

[0126] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0127] The computer-readable storage medium may be included in the hearing aid, or may exist independently without being installed in the hearing aid.

[0128] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the hearing aid, the hearing aid: obtains usage data of each electronic device, wherein the usage data includes usage frequency, usage duration, and usage function;

[0129] Perform prediction based on the usage data using a prediction model to obtain a target electronic device;

[0130] When it is determined that the hearing aid is lost, a positioning signal of the time of loss is sent to the target electronic device, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

[0131] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0132] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0134] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned search method for hearing aids, and can solve the technical problem of high difficulty in searching for lost hearing aids. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the search method for hearing aids provided by the above-mentioned embodiments, and will not be elaborated here.

[0135] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the above-mentioned search method applied to a hearing aid are implemented.

[0136] The computer program product provided by the present application can solve the technical problem of high difficulty in searching for lost hearing aids. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the searching method for hearing aids provided by the above embodiment, which will not be elaborated here.

[0137] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for searching hearing aids, characterized in that: The search method applied to the hearing aid comprises: Acquire usage data of each electronic device, wherein the usage data includes usage frequency, usage duration, and usage function; Perform prediction based on the usage data using a prediction model to obtain a target electronic device; When it is determined that the hearing aid is lost, a positioning signal of the time of loss is sent to the target electronic device, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

2. The method for searching hearing aids according to claim 1, wherein: Before the step of predicting based on the usage data by using a prediction model to obtain a target electronic device, the method includes: Acquire historical usage data of each electronic device and a corresponding historical target electronic device, wherein the historical usage data includes historical usage frequency, historical usage duration, and historical usage function; The historical usage data and the historical target electronic devices are trained to obtain a prediction model for screening target electronic devices.

3. The method for searching hearing aids according to claim 1, wherein: The method of determining a target electronic device also includes: Scoring each electronic device according to a preset rule to obtain a scoring result, wherein the attributes measured by the preset rule include the usage time, online time, preset usage probability, signal penetration capability and signal strength of each electronic device; The target electronic device is screened based on the scoring result.

4. The method for searching hearing aids according to claim 3, wherein: Before the step of obtaining the scoring result, the following steps are included: Recording interaction data with each electronic device, wherein the interaction data includes the amount of interaction data and the number of connections; The degree of dependence on each electronic device is determined according to the interaction data, and the scoring weight of the preset rule is adjusted according to the degree of dependence.

5. The method for searching hearing aids according to claim 4, wherein: The types of interaction data include direct interaction data and indirect interaction data. The step of recording the interaction data with each electronic device includes: If the interaction with each electronic device is carried out through a wireless connection, the data generated is direct interaction data; If the user interacts with each electronic device through voice commands, the data generated is indirect interaction data.

6. The method for searching hearing aids according to claim 1, wherein: The search method applied to hearing aids also includes: Determine whether you are outdoors based on location data; If the device is outdoors and is determined to be lost, the historical loss data and historical behavior data at the time of loss are obtained; By presetting the neural network model, the probability of loss under the preset behavior is obtained; When a preset behavior is detected, a reminder will be lost.

7. A search device for a hearing aid, characterized in that: The search device for hearing aids comprises: An acquisition module, used to acquire usage data of each electronic device, wherein the usage data includes usage frequency, usage duration and usage function; A prediction module, configured to make a prediction based on the usage data by using a prediction model to obtain a target electronic device; The search module is used to send a positioning signal of the time of loss to the target electronic device when the hearing aid is determined to be lost, wherein the target electronic device is used to prompt the lost location of the hearing aid at the time of loss.

8. A hearing aid, characterized in that: The hearing aid comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the search method applied to the hearing aid according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the search method applied to a hearing aid as claimed in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the search method for a hearing aid according to any one of claims 1 to 6 are implemented.

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