CN117373614A - Finger health training method, system and storage medium based on wearing product - Google Patents
Finger health training method, system and storage medium based on wearing product Download PDFInfo
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Abstract
The invention discloses a finger health training method, a system and a storage medium based on a wearable product, wherein the method comprises the following steps: generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product; acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details; displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product; and updating the rehabilitation training data based on the training feedback data to output a training index. The invention can follow the medical detection mode method on the finger health detection project based on the wearing product so as to achieve the purpose of preliminary judgment and rehabilitation advice, and aims to bring comprehensive health conservation to users.
Description
Technical Field
The invention relates to the technical field of intelligent wearing, in particular to a finger health training method, a system and a storage medium based on wearing products.
Background
Smart wearable devices are becoming popular for consumption, such as smart watches or smart bracelets, but on the market at present, health monitoring of wearable products is mainly focused on heart rate, blood oxygen, sleep and exercise, and blood pressure and blood sugar technologies are still not mature.
However, as the internet products are more and more abundant, the life style of people also greatly changes, and the dependence on mobile phones or other electronic products is more and more increased, such as daily video brushing and playing time is longer and longer, the risks of tendinitis and tenosynovitis are higher and higher, and the products which are used for detecting and making rehabilitation advice are also lacking in the subdivided healthy plates.
Disclosure of Invention
The invention aims to provide a finger health training method, a system and a storage medium based on a wearing product, wherein the wearing product can follow a medical detection mode method on a finger health detection project so as to achieve the purpose of preliminary judgment and rehabilitation advice, and aims to bring comprehensive health conservation to users.
The first aspect of the invention provides a finger health training method based on wearing products, which comprises the following steps:
generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product;
acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product;
and updating the rehabilitation training data based on the training feedback data to output a training index.
In this scheme, generate healthy test data in order to utilize wearing product to show to obtain the test feedback data of user on wearing product, specifically include:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
In this scheme, based on the test feedback data obtain user health details to based on user health details generate rehabilitation training data, specifically include:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
In this scheme, based on rehabilitation training data utilizes wearing product to show to obtain the training feedback data of user on wearing product, specifically include:
based on the rehabilitation training data, carrying out visual display in combination with different natural times, wherein the rehabilitation training data comprises finger massage training, finger stretch and bend training, paper cup training and roller training;
and acquiring training feedback operation data of a user on the wearable product based on different rehabilitation training data to obtain the training feedback data.
In this scheme, based on the training feedback data, update the rehabilitation training data to output training indexes, specifically including:
updating the rehabilitation training data based on the training feedback data in combination with a corresponding health threshold, wherein,
if the corresponding user operation in the training feedback data meets the health threshold, indicating that the current rehabilitation training meets the standard;
the corresponding user operation in the training feedback data does not meet the health threshold, and the current rehabilitation training is not up to standard;
and outputting the training index based on the standard-reaching and standard-falling training data, wherein the training index comprises an index detail table and an index completion degree.
In this scheme, the method further includes performing data sharing based on a preset communication mechanism, where the shared data includes the user health details, the training rehabilitation data, and the training index.
The second aspect of the present invention also provides a finger health training system based on a wearable product, comprising a memory and a processor, wherein the memory comprises a finger health training method program based on the wearable product, and the processor executes the finger health training method program based on the wearable product to realize the following steps:
generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product;
acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product;
and updating the rehabilitation training data based on the training feedback data to output a training index.
In this scheme, generate healthy test data in order to utilize wearing product to show to obtain the test feedback data of user on wearing product, specifically include:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
In this scheme, based on the test feedback data obtain user health details to based on user health details generate rehabilitation training data, specifically include:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
In this scheme, based on rehabilitation training data utilizes wearing product to show to obtain the training feedback data of user on wearing product, specifically include:
based on the rehabilitation training data, carrying out visual display in combination with different natural times, wherein the rehabilitation training data comprises finger massage training, finger stretch and bend training, paper cup training and roller training;
and acquiring training feedback operation data of a user on the wearable product based on different rehabilitation training data to obtain the training feedback data.
In this scheme, based on the training feedback data, update the rehabilitation training data to output training indexes, specifically including:
updating the rehabilitation training data based on the training feedback data in combination with a corresponding health threshold, wherein,
if the corresponding user operation in the training feedback data meets the health threshold, indicating that the current rehabilitation training meets the standard;
the corresponding user operation in the training feedback data does not meet the health threshold, and the current rehabilitation training is not up to standard;
and outputting the training index based on the standard-reaching and standard-falling training data, wherein the training index comprises an index detail table and an index completion degree.
In this scheme, implementing the finger health training method program based on the wearable product when executed by the processor further includes performing data sharing based on a preset communication mechanism, where the shared data includes the user health details, the training rehabilitation data, and the training index.
A third aspect of the present invention provides a computer readable storage medium, where the computer readable storage medium includes a machine-based finger health training method program, where the method program is executed by a processor to implement a method for training finger health of a wearable product according to any one of the above steps.
The invention discloses a finger health training method, a finger health training system and a finger health training storage medium based on a wearing product, which can follow a medical detection mode method on a finger health detection project based on the wearing product so as to achieve the purpose of preliminary judgment and rehabilitation advice, and aims to bring comprehensive health conservation, particularly health detection and rehabilitation training of tenosynovitis and tenosynovitis to users.
Drawings
FIG. 1 shows a flow chart of a finger health training method based on a wearable product of the present invention;
fig. 2 shows a block diagram of a finger health training system based on a wearable product according to the invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
Fig. 1 shows a flowchart of a finger health training method based on a wearable product.
As shown in fig. 1, the application discloses a finger health training method based on wearing products, which comprises the following steps:
s102, generating health test data to display by using a wearing product, and acquiring test feedback data of a user on the wearing product;
s104, acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
s106, displaying by using the wearable product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearable product;
s108, updating the rehabilitation training data based on the training feedback data to output a training index.
It should be noted that, in this embodiment, first, it is required to test finger health of a user and then output corresponding training data for a problem occurring after the test, so that the user performs rehabilitation training, specifically, first, health test data is generated to display by using a wearable product and test feedback data of the user on the wearable product is obtained, so that whether the user has tendinitis and/or tenosynovitis loss is identified based on the test feedback data, that is, based on the test feedback data, if so, user health details are obtained, rehabilitation training data is generated based on the user health details, so that the rehabilitation training data is displayed by using the wearable product and training feedback data of the user on the wearable product is obtained, so that training indexes are updated based on the training feedback data to output training indexes for the user to perform supervision training, wherein the training indexes can provide the user with more obvious information about which rehabilitation training is completed, which is incomplete, and the change amount of the rehabilitation degree, so that the user can grasp the latest finger health in real time.
According to an embodiment of the present invention, the generating health test data to display by using a wearable product and obtaining test feedback data of a user on the wearable product specifically includes:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
It should be noted that, in this embodiment, for tendinitis and/or tenosynovitis detection, corresponding health basic items are detected, that is, the health test data is generated based on the health item basic parameters, so that visual scene display is performed by using the wearable product based on the health test data, where the visual scene includes a pressing scene, a drawing scene and a reaction speed scene, and by generating different visual scenes for a user to perform a test, test operation data of the user on the wearable product can be obtained to obtain corresponding test feedback data, where the test feedback data obtained in different scenes are different, and the test operations such as clicking (single point, multiple point), pressing, drawing and other operations.
According to an embodiment of the present invention, the method for acquiring user health details based on the test feedback data and generating rehabilitation training data based on the user health details specifically includes:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
It should be noted that, in this embodiment, under different visual scenes, the test feedback data corresponding to the user may fall on different health thresholds, so the user health details need to be obtained based on the test feedback data under different visual scenes and the health thresholds under the corresponding scenes, where the different health thresholds correspond to different health levels, for example, how many times are pressed in a specified time under a pressing scene, and how much pressing force is; or drawing a scene, drawing length in a specified time, and drawing accuracy; or the reaction speed scene, the number of times of capturing the dynamic target point successfully in the specified time, and the like, correspond to different user health details based on different test feedback data, and correspondingly, different corresponding health grades of the threshold values are different, so that parameters which do not meet the preset grades can be extracted based on the user health details to serve as parameters to be trained, all the parameters to be trained which do not meet the corresponding grades are input into a trained neural network model in a collecting mode to obtain the rehabilitation training data, for example, under a pressing scene, the parameters which do not meet the preset grades are extracted when the pressing frequency is less than 15 times in 30s, for example, the drawing scene, the parameters to be trained in the different scenes are also extracted to not meet the preset grades when the drawing accuracy is less than 80 percent in 30s, the parameters to be trained in the different scenes are input into the neural network model, the parameters to be trained are distributed to corresponding neural units including, for example, the pressing neurons and the reaction speed neurons, and the corresponding rehabilitation training data can be obtained according to different data through iterative training of the neural network model.
According to an embodiment of the present invention, the displaying based on the rehabilitation training data by using a wearable product and acquiring training feedback data of a user on the wearable product specifically includes:
based on the rehabilitation training data, carrying out visual display in combination with different natural times, wherein the rehabilitation training data comprises finger massage training, finger stretch and bend training, paper cup training and roller training;
and acquiring training feedback operation data of a user on the wearable product based on different rehabilitation training data to obtain the training feedback data.
It should be noted that, in this embodiment, the rehabilitation training data includes finger massage training, finger stretch training, paper cup training and roller training, when the wearable product is used for displaying, different natural times are needed to be combined to visually display the training, for example, the finger massage training corresponds to reminding training, the first reminding should be performed in the day of the natural day, the finger stretch training, paper cup training and roller training corresponds to training tasks generated in the wearable product, then reasonable allocation can be performed according to different time periods, and then training feedback operation data of a user on the wearable product is obtained based on different rehabilitation training data, for example, the finger stretch training can be obtained by obtaining feedback operation of the user on a visual display interactive interface.
According to an embodiment of the present invention, the updating the rehabilitation training data based on the training feedback data to output a training index specifically includes:
updating the rehabilitation training data based on the training feedback data in combination with a corresponding health threshold, wherein,
if the corresponding user operation in the training feedback data meets the health threshold, indicating that the current rehabilitation training meets the standard;
the corresponding user operation in the training feedback data does not meet the health threshold, and the current rehabilitation training is not up to standard;
and outputting the training index based on the standard-reaching and standard-falling training data, wherein the training index comprises an index detail table and an index completion degree.
It should be noted that, in this embodiment, different training data correspond to different health thresholds, so that the judgment is also made based on the operation data of the user, that is, the rehabilitation training data is updated based on the training feedback data in combination with the corresponding health threshold, where,
if the corresponding user operation in the training feedback data meets the health threshold, the current rehabilitation training is up to standard, if the corresponding user operation in the training feedback data does not meet the health threshold, the current rehabilitation training is up to standard, the training index is output based on the up to standard and up to standard training data, wherein the training index comprises an index detail table and an index completion degree, namely, specific information of different training feedback is calculated to obtain the training index.
According to the embodiment of the invention, the method further comprises data sharing based on a preset communication mechanism, wherein the shared data comprises the user health details, the training rehabilitation data and the training indexes.
It should be noted that, in this embodiment, since the wearable product may interact with the cloud background, data sharing may be performed based on a preset communication mechanism, where the shared data includes the user health details, the training rehabilitation data, and the training indexes, so that multiple users may perform data sharing, especially for the elderly living alone, the risk of tendinitis and tenosynovitis is very high, and children or relatives of the elderly living alone may remotely review the test rehabilitation result through data sharing, so as to help users monitor and promote user experience.
Fig. 2 shows a block diagram of a finger health training system based on a wearable product according to the invention.
As shown in fig. 2, the invention discloses a finger health training system based on a wearing product, which comprises a memory and a processor, wherein the memory comprises a finger health training method program based on the wearing product, and the following steps are realized when the finger health training method program based on the wearing product is executed by the processor:
generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product;
acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product;
and updating the rehabilitation training data based on the training feedback data to output a training index.
It should be noted that, in this embodiment, first, it is required to test finger health of a user and then output corresponding training data for a problem occurring after the test, so that the user performs rehabilitation training, specifically, first, health test data is generated to display by using a wearable product and test feedback data of the user on the wearable product is obtained, so that whether the user has tendinitis and/or tenosynovitis loss is identified based on the test feedback data, that is, based on the test feedback data, if so, user health details are obtained, rehabilitation training data is generated based on the user health details, so that the rehabilitation training data is displayed by using the wearable product and training feedback data of the user on the wearable product is obtained, so that training indexes are updated based on the training feedback data to output training indexes for the user to perform supervision training, wherein the training indexes can provide the user with more obvious information about which rehabilitation training is completed, which is incomplete, and the change amount of the rehabilitation degree, so that the user can grasp the latest finger health in real time.
According to an embodiment of the present invention, the generating health test data to display by using a wearable product and obtaining test feedback data of a user on the wearable product specifically includes:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
It should be noted that, in this embodiment, for tendinitis and/or tenosynovitis detection, corresponding health basic items are detected, that is, the health test data is generated based on the health item basic parameters, so that visual scene display is performed by using the wearable product based on the health test data, where the visual scene includes a pressing scene, a drawing scene and a reaction speed scene, and by generating different visual scenes for a user to perform a test, test operation data of the user on the wearable product can be obtained to obtain corresponding test feedback data, where the test feedback data obtained in different scenes are different, and the test operations such as clicking (single point, multiple point), pressing, drawing and other operations.
According to an embodiment of the present invention, the method for acquiring user health details based on the test feedback data and generating rehabilitation training data based on the user health details specifically includes:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
It should be noted that, in this embodiment, under different visual scenes, the test feedback data corresponding to the user may fall on different health thresholds, so the user health details need to be obtained based on the test feedback data under different visual scenes and the health thresholds under the corresponding scenes, where the different health thresholds correspond to different health levels, for example, how many times are pressed in a specified time under a pressing scene, and how much pressing force is; or drawing a scene, drawing length in a specified time, and drawing accuracy; or the reaction speed scene, the number of times of capturing the dynamic target point successfully in the specified time, and the like, correspond to different user health details based on different test feedback data, and correspondingly, different corresponding health grades of the threshold values are different, so that parameters which do not meet the preset grades can be extracted based on the user health details to serve as parameters to be trained, all the parameters to be trained which do not meet the corresponding grades are input into a trained neural network model in a collecting mode to obtain the rehabilitation training data, for example, under a pressing scene, the parameters which do not meet the preset grades are extracted when the pressing frequency is less than 15 times in 30s, for example, the drawing scene, the parameters to be trained in the different scenes are also extracted to not meet the preset grades when the drawing accuracy is less than 80 percent in 30s, the parameters to be trained in the different scenes are input into the neural network model, the parameters to be trained are distributed to corresponding neural units including, for example, the pressing neurons and the reaction speed neurons, and the corresponding rehabilitation training data can be obtained according to different data through iterative training of the neural network model.
According to an embodiment of the present invention, the displaying based on the rehabilitation training data by using a wearable product and acquiring training feedback data of a user on the wearable product specifically includes:
based on the rehabilitation training data, carrying out visual display in combination with different natural times, wherein the rehabilitation training data comprises finger massage training, finger stretch and bend training, paper cup training and roller training;
and acquiring training feedback operation data of a user on the wearable product based on different rehabilitation training data to obtain the training feedback data.
It should be noted that, in this embodiment, the rehabilitation training data includes finger massage training, finger stretch training, paper cup training and roller training, when the wearable product is used for displaying, different natural times are needed to be combined to visually display the training, for example, the finger massage training corresponds to reminding training, the first reminding should be performed in the day of the natural day, the finger stretch training, paper cup training and roller training corresponds to training tasks generated in the wearable product, then reasonable allocation can be performed according to different time periods, and then training feedback operation data of a user on the wearable product is obtained based on different rehabilitation training data, for example, the finger stretch training can be obtained by obtaining feedback operation of the user on a visual display interactive interface.
According to an embodiment of the present invention, the updating the rehabilitation training data based on the training feedback data to output a training index specifically includes:
updating the rehabilitation training data based on the training feedback data in combination with a corresponding health threshold, wherein,
if the corresponding user operation in the training feedback data meets the health threshold, indicating that the current rehabilitation training meets the standard;
the corresponding user operation in the training feedback data does not meet the health threshold, and the current rehabilitation training is not up to standard;
and outputting the training index based on the standard-reaching and standard-falling training data, wherein the training index comprises an index detail table and an index completion degree.
It should be noted that, in this embodiment, different training data correspond to different health thresholds, so that the judgment is also made based on the operation data of the user, that is, the rehabilitation training data is updated based on the training feedback data in combination with the corresponding health threshold, where,
if the corresponding user operation in the training feedback data meets the health threshold, the current rehabilitation training is up to standard, if the corresponding user operation in the training feedback data does not meet the health threshold, the current rehabilitation training is up to standard, the training index is output based on the up to standard and up to standard training data, wherein the training index comprises an index detail table and an index completion degree, namely, specific information of different training feedback is calculated to obtain the training index.
According to the embodiment of the invention, the method further comprises data sharing based on a preset communication mechanism, wherein the shared data comprises the user health details, the training rehabilitation data and the training indexes.
It should be noted that, in this embodiment, since the wearable product may interact with the cloud background, data sharing may be performed based on a preset communication mechanism, where the shared data includes the user health details, the training rehabilitation data, and the training indexes, so that multiple users may perform data sharing, especially for the elderly living alone, the risk of tendinitis and tenosynovitis is very high, and children or relatives of the elderly living alone may remotely review the test rehabilitation result through data sharing, so as to help users monitor and promote user experience.
A third aspect of the present invention provides a computer readable storage medium, where the computer readable storage medium includes a wearable product-based finger health training method program, where the wearable product-based finger health training method program, when executed by a processor, implements the steps of a wearable product-based finger health training method as described in any one of the above.
The invention discloses a finger health training method, a finger health training system and a finger health training storage medium based on a wearing product, which can follow a medical detection mode method on a finger health detection project based on the wearing product so as to achieve the purpose of preliminary judgment and rehabilitation advice, and aims to bring comprehensive health conservation, particularly health detection and rehabilitation training of tenosynovitis and tenosynovitis to users.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (10)
1. The finger health training method based on the wearable product is characterized by comprising the following steps of:
generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product;
acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product;
and updating the rehabilitation training data based on the training feedback data to output a training index.
2. The method for training finger health based on wearing products according to claim 1, wherein the generating health test data for displaying by using the wearing products and obtaining test feedback data of users on the wearing products specifically comprises:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
3. The method for training finger health based on wearable products according to claim 2, wherein the step of obtaining user health details based on the test feedback data and generating rehabilitation training data based on the user health details specifically comprises the steps of:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
4. The method for measuring finger health based on wearing products according to claim 3, wherein the method for displaying the rehabilitation training data based on the wearing products and obtaining training feedback data of the user on the wearing products specifically comprises the following steps:
based on the rehabilitation training data, carrying out visual display in combination with different natural times, wherein the rehabilitation training data comprises finger massage training, finger stretch and bend training, paper cup training and roller training;
and acquiring training feedback operation data of a user on the wearable product based on different rehabilitation training data to obtain the training feedback data.
5. The method for training finger health based on wearable products according to claim 4, wherein updating the rehabilitation training data based on the training feedback data to output training indexes comprises:
updating the rehabilitation training data based on the training feedback data in combination with a corresponding health threshold, wherein,
if the corresponding user operation in the training feedback data meets the health threshold, indicating that the current rehabilitation training meets the standard;
the corresponding user operation in the training feedback data does not meet the health threshold, and the current rehabilitation training is not up to standard;
and outputting the training index based on the standard-reaching and standard-falling training data, wherein the training index comprises an index detail table and an index completion degree.
6. The method of claim 5, further comprising sharing data based on a preset communication mechanism, wherein the shared data comprises the user health details, training rehabilitation data and training indicators.
7. The finger health training system based on the wearable product is characterized by comprising a memory and a processor, wherein the memory comprises a finger health training method program based on the wearable product, and the method realizes the following steps when the finger health training method program based on the wearable product is executed by the processor:
generating health test data to display by using the wearing product, and acquiring test feedback data of a user on the wearing product;
acquiring user health details based on the test feedback data, and generating rehabilitation training data based on the user health details;
displaying by using a wearing product based on the rehabilitation training data, and acquiring training feedback data of a user on the wearing product;
and updating the rehabilitation training data based on the training feedback data to output a training index.
8. The wearable product-based finger health training system of claim 7, wherein the generating health test data for display with the wearable product and obtaining test feedback data of a user on the wearable product specifically comprises:
generating the health test data based on health item base parameters;
based on the health test data, utilizing the wearable product to display a visual scene, wherein the visual scene comprises a pressing scene, a drawing scene and a reaction speed scene;
and obtaining corresponding test feedback data based on the test operation data of the user on the wearable product in different visual scenes.
9. The wearable product-based finger health training system of claim 8, wherein the acquiring the user health details based on the test feedback data and generating the rehabilitation training data based on the user health details specifically comprises:
obtaining the user health details based on the test feedback data in different visual scenes and health thresholds in corresponding scenes, wherein different health thresholds correspond to different health levels;
and extracting parameters which do not meet a preset grade based on the user health details as parameters to be trained, and inputting all the parameters to be trained which do not meet the corresponding grade into a trained neural network model in a collecting way to obtain the rehabilitation training data.
10. A computer readable storage medium, wherein the computer readable storage medium includes a wearable product-based finger health training method program, and when the wearable product-based finger health training method program is executed by a processor, the steps of the wearable product-based finger health training method according to any one of claims 1 to 6 are implemented.
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