Mask selection method and system, electronic device, computer program product

Abstract

The embodiment of the present application provides a kind of selection method and selection system of mask, electronic equipment, computer program product, belong to medical instrument field.The selection method includes: according to the result of user's questionnaire, one or more mask types of first user preference are selected;According to the subjective questionnaire result, the first score of each specification mask corresponding to each model under each mask type of the first user preference is obtained by scoring each specification mask corresponding to each model under each mask type of the first user preference;According to the face scanning data of user and the preset score of the face data of the mask of the first user preference, the second score of each specification mask of second user preference is obtained;And, according to the first score and the second score, the mask of target specification corresponding to target model under target mask type is determined.The technical scheme of the present application realizes more accurate mask recommendation, and can effectively improve the satisfaction of user.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and more specifically to a method for selecting a face mask, a face mask selection system, an electronic device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] In modern medicine, the treatment of respiratory diseases increasingly relies on ventilation therapy equipment, especially the design and fit of face masks, which directly affect treatment outcomes. Ventilation therapy is commonly used to treat patients with conditions such as sleep apnea and chronic obstructive pulmonary disease (COPD). The suitability of the face mask not only affects patient comfort but also the effective delivery of airflow and the therapeutic effect. Traditional ventilation mask designs often use standardized sizes and shapes, but each patient's facial structure varies significantly, including mouth height, eye spacing, and nose height. Such a generic design may lead to a mismatch between the mask and facial contours, causing airflow leakage, reducing treatment efficiency, and even causing patient discomfort and refusal to wear the mask. Therefore, developing a method that can recommend a suitable face mask based on individual facial characteristics is crucial.

[0003] In recent years, with advancements in 2D and 3D imaging technologies and facial scanning techniques, the possibility of utilizing facial data science for mask selection and personalized mask design has been increasing. These technologies can accurately acquire a user's facial structure, providing detailed biometric data, which in turn provides a basis for optimizing ventilation therapy equipment. By analyzing the proportions of a user's facial features, a custom-made mask can be recommended to the patient, thereby improving wearing comfort and treatment effectiveness. Therefore, there is an urgent need for a more precise mask recommendation method to improve user satisfaction. Summary of the Invention

[0004] The purpose of this invention is to provide a method for selecting a face mask, a system for selecting a face mask, an electronic device, a computer-readable storage medium, and a computer program product. This method for selecting a face mask can solve the technical problem that existing technologies cannot provide users (or patients) with face masks that are more accurately suited to their habits and facial size.

[0005] To achieve the above objectives, the present invention provides a method for selecting a face mask, comprising: selecting one or more face mask types preferred by a first user from all types of face masks based on user survey questionnaire results, wherein each face mask type includes multiple models, each model includes multiple specifications, and the survey questionnaire results include subjective questionnaire results; scoring each specification of face mask corresponding to each model under each face mask type preferred by the first user based on the subjective questionnaire results to obtain a first score for each specification of face mask corresponding to each model under each face mask type preferred by the first user; obtaining a second score for each specification of face mask corresponding to each model under each face mask type preferred by a second user based on preset scores corresponding to user facial scan data and facial data of face masks of each specification of face mask preferred by the first user; and determining a target specification of face mask corresponding to a target model under a target face mask type based on the first score and the second score.

[0006] Optionally, obtaining the second score for each model of each mask type under the second user's preferred mask based on the user's facial scan data and the preset score corresponding to the facial data of each mask type of the first user's preferred mask includes: obtaining the facial data of each mask type of the first user's preferred mask based on the facial data of each model of the first user's preferred mask; assigning preset scores to the facial data of each mask type of the first user's preferred mask; and obtaining the second score for each model of each mask type under the second user's preferred mask based on the preset scores corresponding to the facial data of each mask type of the first user's preferred mask and the user's facial scan data.

[0007] Optionally, the step of obtaining a second score for each model of each mask type under the second user preference based on the preset score corresponding to the facial data of each mask type of the first user preference and the user's facial scan data includes: comparing the user's facial scan data with the range of each mask type of the first user preference, and obtaining a third score corresponding to when the user's facial scan data falls within the facial data of each mask type of the first user preference; and determining each mask type of each model under each type corresponding to the third score as the mask of the second user preference.

[0008] The third score corresponding to the mask preferred by the second user is determined as the second score for each model and specification of mask under each mask type preferred by the second user.

[0009] Optionally, determining the target specification of the mask corresponding to the target model under the target mask type based on the first score and the second score includes: comparing the first score and the second score of masks belonging to the same mask type, the same model, and the same specification, and filtering out the mask with the larger value between the first score and the second score; when the number of masks with the larger value is one, determining the mask with the larger value as the mask corresponding to the target specification of the target model under the target mask type; or, when the number of masks with the larger value is multiple, sorting the multiple masks with the larger values, and determining a specific number of masks as the mask corresponding to the target specification of the target model under the target mask type.

[0010] Optionally, when the first score and the second score respectively correspond to multiple specifications of a single model or multiple specifications of multiple models of face masks, the step of determining the target specification of the target model under the target face mask type based on the first score and the second score further includes: weighting and summing the first score and the second score of face masks belonging to the same face mask type, the same model, and the same specification to obtain multiple comprehensive scores; sorting the multiple comprehensive scores, and determining a specific number of face masks as the target specification of the target model under the target face mask type.

[0011] Optionally, the subjective questionnaire results include multiple preset questions. The step of scoring each model of each mask corresponding to each specification under each mask type preferred by the first user based on the subjective questionnaire results to obtain a first score for each model of each specification of mask under each mask type preferred by the first user includes: scoring each preset question from multiple evaluation dimensions based on the subjective questionnaire results to obtain scores corresponding to the multiple preset questions under multiple evaluation dimensions; determining the average score of the multiple preset questions under each evaluation dimension based on the scores corresponding to the multiple preset questions under the multiple evaluation dimensions; and obtaining a first score for each model of mask corresponding to each specification of mask based on the average score of the multiple preset questions under each evaluation dimension and the preset weight corresponding to each model of mask.

[0012] Optionally, the survey results also include objective survey results. Selecting one or more types of face masks preferred by the first user from all types of face masks based on the user's survey results includes: selecting face masks that conform to the objective survey results from all types of face masks based on the objective survey results, thereby obtaining one or more types of face masks preferred by the first user.

[0013] A second aspect of the present invention also provides a face mask selection system, comprising: a selection module, configured to select one or more face mask types preferred by a first user from all types of face masks based on user questionnaire results, wherein each face mask type includes multiple models, each model includes multiple specifications, and the questionnaire results include subjective questionnaire results; a first acquisition module, configured to score each specification of face mask corresponding to each model under each face mask type preferred by the first user based on the subjective questionnaire results, to obtain a first score for each specification of face mask corresponding to each model under each face mask type preferred by the first user; a second acquisition module, configured to obtain a second score for each specification of face mask corresponding to each model under each face mask type preferred by the second user based on preset scores corresponding to user facial scan data and facial data of each specification of face mask preferred by the first user; and a determination module, configured to determine the target specification of face mask corresponding to the target model under the target face mask type based on the first score and the second score.

[0014] A third aspect of the present invention also provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory storing computer-executable instructions; the processor executing the computer-executable instructions stored in the memory to implement the mask selection method as described above.

[0015] A fourth aspect of the present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the mask selection method as described above.

[0016] A fifth aspect of the present invention is a computer program product, comprising a computer program that, when executed by a processor, implements the mask selection method as described above.

[0017] Through the above technical solution, based on the user's questionnaire results, one or more mask types preferred by the first user are selected from all types of masks. Each mask type includes multiple models, and each model includes multiple specifications. The questionnaire results include subjective questionnaire results. Based on the subjective questionnaire results, a score is assigned to each specification of mask corresponding to each model under each mask type preferred by the first user to obtain a first score for each specification of mask corresponding to each model under each mask type preferred by the first user. Based on the user's facial scan data and the preset score corresponding to the facial data of each specification of mask preferred by the first user, a second score is obtained for each specification of mask corresponding to each model under each mask type preferred by the second user. Finally, based on the first score and the second score, the target specification of mask corresponding to the target model under the target mask type is determined.

[0018] The technical solution provided by this invention performs an initial screening of all mask types based on user survey questionnaire results, eliminating mask types that do not meet user preferences to obtain a first set of preferred mask types. Then, based on the subjective questionnaire results, all models and specifications of the selected first set of preferred mask types are scored to obtain a first score. Next, based on the user's facial scan data and the preset scores corresponding to the facial data of each specification of the first set of preferred masks, a second score corresponding to the user's scan data is obtained. Finally, by combining the first score from the subjective questionnaire and the second score corresponding to the user's facial scan data, the specific mask type, its corresponding model, and its specific specifications are determined. This technical solution considers both the user's subjective needs and each user's facial data, achieving more accurate mask recommendations and effectively improving user satisfaction.

[0019] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0020] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0021] Figure 1 This is a flowchart of a method for selecting a face mask according to the first embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram illustrating the acquisition of a user's facial data using a two-dimensional scanning method;

[0023] Figure 3 This is a schematic diagram of obtaining a user's facial scan data provided in the first embodiment of the present invention;

[0024] Figure 4 The second embodiment of the present invention provides a structural diagram of a mask selection system. Detailed Implementation

[0025] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0026] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0027] Figure 1 This is a flowchart of a face mask selection method provided in the first embodiment of the present invention. A face mask selection method includes the following steps S10-S13.

[0028] In step S10, based on the results of the user's questionnaire, one or more types of face masks preferred by the first user are selected from all types of face masks.

[0029] Each type of face mask includes multiple models, and each model includes multiple specifications. The survey results include subjective questionnaire results.

[0030] For example, this embodiment of the invention uses a medical respiratory mask. Commercially available masks typically include various types, such as full-face masks, nasal masks, mouth-nose masks, and nasal pillow masks. Each type of mask can be further divided into multiple models due to differences in materials, the proportion of the eyes, nose, and mouth, and performance. For example, full-face masks are divided into models A1, A2, ..., An, etc. Similarly, nasal masks are divided into models B1, B2, B3, etc. Other mask types are similar and will not be elaborated upon here. Each model of mask is further divided into small, medium, and large sizes.

[0031] Furthermore, the survey results also include objective survey results. The step of selecting one or more types of face masks preferred by the first user from all types of face masks based on the user's survey results includes: selecting face masks that match the objective survey results from all types of face masks based on the objective survey results, thereby obtaining one or more types of face masks preferred by the first user.

[0032] For example, in order to select face masks with high satisfaction for users (or patients), this embodiment of the invention obtains basic user information through a questionnaire to gain a more comprehensive understanding of user preferences. For example, a questionnaire is prepared in advance for users to complete simply, and the questionnaire results for the current user are obtained. The questionnaire results include objective questionnaire results, which are mainly strongly correlated questionnaires with relatively objective questions. These questions mainly target the most critical factors in face mask selection, such as sleeping posture (side-lying or supine), breathing method (nasal breathing or mouth breathing), whether there is an allergy to a certain material, facial shape, whether there is rhinitis, mouth breathing habits, etc. Through objective questionnaire results, face mask types that are not suitable for the user can be excluded from all types of face masks available in the hospital. The remaining face mask types may be one or more, that is, one or more face mask types preferred by the first user are selected.

[0033] This invention allows for preliminary screening and elimination of unsuitable face masks by conducting basic user surveys, thus helping to provide users with face masks that offer higher satisfaction.

[0034] In step S11, based on the results of the subjective questionnaire, a score is assigned to each model of each mask corresponding to each specification of each mask under each mask type preferred by the first user, so as to obtain the first score of each model of each specification of mask under each mask type preferred by the first user.

[0035] For example, the user survey also includes a subjective questionnaire section, which is a weakly correlated questionnaire. This section mainly involves asking highly subjective questions, such as sleep quality and skin sensitivity. These questions involve some auxiliary factors, such as comfort preferences when wearing the mask and material selection. Although these factors have a relatively small impact on the suitability of the mask, they help to further refine the mask recommendations.

[0036] Furthermore, the subjective questionnaire results include multiple preset questions. The step of scoring each specification of face mask corresponding to each model under each type of face mask preferred by the first user based on the subjective questionnaire results to obtain the first score of each specification of face mask corresponding to each model under each type of face mask preferred by the first user can be referred to in the following steps S111-S113.

[0037] In step S111, based on the results of the subjective questionnaire, each preset question in the multiple preset questions is scored from multiple evaluation dimensions to obtain the scores corresponding to the multiple preset questions under multiple evaluation dimensions.

[0038] For example, the subjective questionnaire results include multiple preset questions, including but not limited to the following: 1. Is your skin sensitive? Do you need a mask that has less contact with your skin? 2. Do you need a mask and padding with better breathability? 3. Do you think a silicone mask is suitable for you? 4. How sensitive are you to airflow? Each question can be further divided into multiple levels, such as classifying the mask contact area into levels one, two, three, four, and five, with higher levels indicating a larger required contact area. Similarly, levels can be set for other questions accordingly, which will not be elaborated here.

[0039] Multiple evaluation dimensions include, but are not limited to, comfort, breathability, sealing, fit, and material. Based on the results of the subjective questionnaire, multiple preset questions are scored across these multiple rating dimensions. For example, each question is divided into five levels, with each rating dimension having a score of 1 to 5. For instance, for the mask contact area, if the user selects level two, the corresponding fit score is 2, comfort is 4, sealing is 3, and breathability is 5, etc. See Table 1 below for details on scoring multiple preset questions across multiple rating dimensions. Since the emphasis of each evaluation dimension differs for each preset question, the scores for each preset question across each evaluation dimension will not be entirely consistent.

[0040]

[0041] Table 1

[0042] In step S112, the average score of the multiple preset questions under each evaluation dimension is determined based on the scores corresponding to the multiple preset questions under the multiple evaluation dimensions.

[0043] For example, this embodiment of the invention uses three preset questions and four evaluation dimensions as examples for explanation and illustration. Specifically, refer to Table 2 for the average scores of multiple preset questions under each rating dimension. The average score here refers to the comprehensive score for each dimension, used to represent the intensity of the user's need in that dimension. For example, an average comfort score of 4.5 indicates that the user has high requirements for comfort, while an average breathability score of 5 indicates that the user has extremely high requirements for breathability.

[0044] Evaluation Dimensions Question 1 score Question 2 score Question 3 (score) … Average score Comfort 4 5 4 / 4.5 Sealing 3 4 4 / 3.5 breathability 5 5 5 / 5.0 Fit 2 2 2 / 2.0

[0045] Table 2

[0046] In step S113, the first score of each specification of the mask corresponding to each model is obtained based on the average score of multiple preset questions under each evaluation dimension and the preset weight corresponding to each specification of the mask for each model.

[0047] For example, suppose the first user prefers multiple types of face masks, including full-face masks, nose masks, and nose pillow masks. Full-face masks include two models, A1 and A2, each further divided into small, medium, and large sizes, resulting in a total of six full-face mask models. Similarly, nose masks include two models, B1 and B2 (not limited to these two), also divided into small, medium, and large sizes (in this embodiment, all sizes are small, medium, and large).

[0048] Because the performance, size, and materials of each type and model of face mask vary, the preset weights are different. For example, the preset weights for the small size of the A1 full-face face mask are 0.4, 0.3, 0.2, and 0.1. The correspondence between these preset weights and multiple evaluation dimensions is as follows: 0.4 corresponds to the average score for comfort, 0.3 to the average score for sealing, 0.2 to the average score for breathability, and 0.1 to fit. The preset weights for the medium size of the A1 full-face face mask are 0.4, 0.4, 0.1, and 0.1. The preset weights for each size of other face mask types have been pre-set and will not be listed here.

[0049] Given the average scores of multiple preset questions under each evaluation dimension in Table 2, these scores are weighted and summed with the preset weights of each specification of mask under the corresponding mask type, resulting in first scores of 3.85 and 3.9 for the two specifications of masks, respectively.

[0050] In step S12, based on the user's facial scan data and the preset score corresponding to the facial data of each specification of mask preferred by the first user, a second score is obtained for each model of each specification of mask under each mask type preferred by the second user.

[0051] The user's facial scan data includes: lip thickness, nasal wing width, and the vertical distance between the corner of the mouth and the eyebrows.

[0052] For example, the user's facial data is first acquired, such as through a two-dimensional or three-dimensional scanning method, or through a photograph of the user. Figure 2 The diagram illustrates the acquisition of user facial data using a two-dimensional scanning method. The horizontal direction represents the first dimension, and the vertical direction represents the second dimension. Figure 3This is a schematic diagram of obtaining a user's facial scan data. The facial scan data includes the user's lip thickness D1 (lip thickness when the mouth is closed), the lip thickness when the mouth is open D1 = upper lip thickness Da + lower lip thickness Db, and also includes the vertical distance D2 between the corner of the mouth and the eyebrows, as well as the width of the nostrils D3.

[0053] Furthermore, the step of obtaining the second score for each model of each mask corresponding to each specification under each mask type preferred by the second user, based on the user's facial scan data and the preset score corresponding to the facial data of each specification of mask preferred by the first user, includes the following steps S121-S123.

[0054] In step S121, facial data for each specification of mask corresponding to each model under each mask type preferred by the first user is obtained.

[0055] For example, facial data for each model and specification of all mask types is pre-stored in the database. This facial data includes, but is not limited to, lip thickness and nose width, nose height, inter-eye distance, vertical distance between the corner of the mouth and eyebrows, a first ratio range for lip thickness to nose width (meaning it is not limited to a fixed ratio; any ratio of the user's lip thickness to nose width within this first ratio range can be used), and a second ratio range for the vertical distance between the corner of the mouth and eyebrows (similar to the aforementioned first ratio range). Preferably, the facial data includes: the first ratio range for lip thickness to nose width and the second ratio range for the nose width and the vertical distance between the corner of the mouth and eyebrows. This embodiment of the invention only requires selecting the mask type preferred by the first user and the facial data for the corresponding model and specification of the mask.

[0056] In step S122, a preset score is assigned to the facial data of each size of mask preferred by the first user.

[0057] For example, in this embodiment of the invention, preset scores can be pre-assigned to all models and specifications of all mask types. The facial data in this embodiment of the invention takes lip thickness, nasal wing width, and the vertical distance between the corner of the mouth and the eyebrow as examples, including a first ratio range of lip thickness to nasal wing width (meaning it is not limited to a fixed ratio; any ratio of the user's lip thickness to nasal wing width within this first ratio range can be used) and a second ratio range of the vertical distance between the corner of the mouth and the eyebrow.

[0058] Preferably, preset scores are assigned to the first ratio range and the second ratio range for each size of face mask preferred by the first user. The first and second ratio ranges are pre-assigned preset scores, and the preset scores corresponding to the first ratio range and the second ratio range for the face mask preferred by the first user are selected from all face masks. Alternatively, preset scores are assigned only to the first ratio range and the second ratio range for each size of face mask preferred by the first user. Table 3 below shows the preset scores assigned to the face mask type preferred by the first user and the corresponding model and size provided by the embodiments of the present invention. The preset score for small size is 3.5 points, for medium size is 4 points, and for large size is 5 points (the preset scores can be set according to actual needs, including but not limited to the listed score values). D1 / D3 represents the first ratio range, and D1 represents the lip thickness (the total thickness of the upper and lower lips when the mouth is closed, i.e., the sum of the upper lip thickness Da and the lower lip thickness Db when the mouth is open, such as...). Figure 3 As shown in the figure, D3 represents the width of the nostrils.

[0059]

[0060] Table 3

[0061] For different types and models of face masks, the first ratio range is only related to the mask specifications. Therefore, for face masks of the same specifications, the preset scores corresponding to the first ratio range are the same. For example, in Table 3, the mask type and model are not considered. The preset scores corresponding to face masks of the same specifications are the same. The preset score for small size is 3.5 points, for medium size is 4 points, and for large size is 5 points. The preset scores can also be adjusted according to actual needs. This embodiment of the invention does not impose specific limitations.

[0062] Similarly, preset values ​​are assigned to the second ratio range. Table 4 is a table showing the preset score relationship between the second ratio range and each specification of face mask provided by the embodiments of the present invention.

[0063]

[0064] Table 4

[0065] In step S123, based on the preset score corresponding to the facial data of each specification of mask in the first user preference and the user's facial scan data, a second score is obtained for each model of each specification of mask under each mask type in the second user preference.

[0066] Further, the second score for each model of each mask corresponding to each specification under each mask type of the second user preference is obtained based on the preset score corresponding to the facial data of each specification of the mask in the first user preference and the user's facial scan data. For details, please refer to the following steps S1211-S1213.

[0067] In step S1211, the user's facial scan data is compared with the facial data of each size of mask preferred by the first user, and a third score is obtained when the user's facial scan data falls into the facial data of each size of mask preferred by the first user.

[0068] For example, since the facial data for each size of mask preferred by the first user corresponds to a preset score, when the user's facial scan data is equal to or approximately equal to the facial data for each size of mask preferred by the first user, it indicates that the user's facial scan data falls within the facial data for each size of mask preferred by the first user, and the preset score corresponding to that size of mask can be obtained, i.e., the third score. Preferably, the third ratio is compared with the first ratio range to obtain the third score corresponding to when the third ratio falls within the first ratio range.

[0069] Preferably, the second score for each model of each mask corresponding to each type of mask preferred by the second user is obtained based on the preset score corresponding to the first ratio range and the first ratio range, the preset score corresponding to the second ratio range and the second ratio range, the third ratio of the user's lip thickness to the width of the nostrils, and the fourth ratio of the user's nostril width to the vertical distance between the corner of the mouth and the eyebrow.

[0070] For example, after obtaining the user's facial data D1, D2, and D3 according to the above steps, the third ratio D1 / D3 can be obtained, for example, the user's third ratio is 0.21. Comparing the third ratio with the first ratio range for each specification of each mask type in Table 3, it can be seen that the data falls within the first ratio range of full-face mask - A1 model - medium size and full-face mask - A2 model - small size, thus obtaining a third score of 4 points and 3.5 points respectively. However, in reality, the third ratio may only fall within the first ratio range of one model and one specification of one mask type, or it may fall within the first ratio range of multiple models and multiple specifications of multiple mask types. This embodiment of the invention is only for explaining its principle and does not limit it.

[0071] Preferably, the fourth ratio is compared with the second ratio range to obtain the fourth score corresponding to the fourth ratio falling within the second ratio range.

[0072] For example, similarly, after obtaining the user's facial data D2 and D3, a fourth ratio D3 / D2 can be obtained. This fourth ratio is then compared with the second ratio range of the face mask. For instance, if the user's fourth ratio (i.e., the width of the nostrils / the vertical distance from the corner of the mouth to the eyebrows) is 0.51, by comparing it with the second ratio range in Table 4, it can be seen that this ratio falls within the second ratio range of both the nose mask - B1 model - small size and the nose pillow mask - H1 model - small size, resulting in a third score of 3.5 for both.

[0073] For example, the masks corresponding to the third score obtained in step S1211 are determined as the second user's preferred masks, namely, the full-face mask-A1 model-medium, the full-face mask-A2 model-small, the nose mask-B1 model-small, and the nose pillow mask-H1 model-small. These four masks are the second user's preferred masks, and further screening will be carried out based on the second user's preferred masks.

[0074] Currently, most face mask selection processes fall into the following categories: 1. Questionnaire only: Users answer questions to select suitable face masks. This method cannot help users choose the size of the face mask, i.e., it cannot select small, medium, or large sizes. 2. Facial scan only: This method can help users select the face mask size, but it cannot select which face mask is suitable for the user; it can only recommend all available face masks to the user. 3. Questionnaire first, then scan: This solution can help recommend face masks and suitable sizes to users, but there is no cross-verification process between the two. If the questionnaire recommendation is inaccurate, the final recommended face mask and size will have significant problems.

[0075] This invention combines a user's facial scan data with a first user-preferred mask, and further filters from the first user-preferred mask to select a second user-preferred mask. This approach considers both the user's personal preferences and objectively filters from the first user-preferred mask using facial data, thus helping to provide users with more satisfactory masks. The terms "first," "second," "third," etc., used in this invention embodiment have no actual meaning and are only used to distinguish different data.

[0076] In step S1213, the third score corresponding to the mask preferred by the second user is determined as the second score of each specification of mask corresponding to each model under each mask type preferred by the second user.

[0077] For example, the third score corresponding to the second user preference in step S1211 is determined as the second score for each model and each size of mask under the mask type of the second user preference. That is, the obtained third score is uniformly recorded as the second score. For example, the third score obtained in step S1211 is 4 points (corresponding to the score of full face mask - A1 model - medium size) and 3.5 points (corresponding to the score of full face mask - A2 model - small size), and the third score obtained in step S1212 is 3.5 points (corresponding to the score of nose mask - B1 model - small size) and 3.5 points (corresponding to the score of nose pillow mask - H1 model - small size). Therefore, the second scores are 4 points, 3.5 points, 3.5 points, and 3.5 points.

[0078] In step S13, based on the first score and the second score, the target specification of the mask corresponding to the target model under the target mask type is determined.

[0079] Further, the step of determining the target specification of the mask corresponding to the target model under the target mask type based on the first score and the second score is specifically referred to in the following steps.

[0080] In step S131, the first score and the second score corresponding to masks of the same type, model and specification are compared, and the mask with the larger value between the first score and the second score is selected.

[0081] For example, assuming that all the masks preferred by the first user are the mask types and corresponding models and specifications in Tables 3 and 4, then there are a total of 12 scores, namely the three scores corresponding to the full face mask-A1 model-small, medium and large sizes, the three scores corresponding to the full face mask-A2 model-small, medium and large sizes, the three scores corresponding to the nose mask-B1 model-small, medium and large sizes, and the three scores corresponding to the nose pillow mask-H1 model-small, medium and large sizes.

[0082] The second score corresponds to the following face masks: Full Face Mask - A1 size - Medium (score 4) and Full Face Mask - A2 size - Small (score 3.5), Nose Mask - B1 size - Small (score 3.5) and Nose Pillow Mask - H1 size - Small (score 3.5).

[0083] Since the first score includes the mask preferred by the first user, and the mask corresponding to the second score is further selected from the masks preferred by the first user, this step only requires comparing the masks included in both the first and second scores. Assume the first scores of the masks obtained in step S11 are as follows: Full-face mask - A1 model - medium size - 3.85 points; Full-face mask - A2 model - small size - 4 points; Nose mask - B1 model - small size - 4.35 points; and Nose pillow mask - H1 model - small size - 4.8 points.

[0084] Only the first and second scores are comparable for masks of the same type, model, and specification. Therefore, the scores for each mask are compared, and the masks with higher scores are selected as follows: Full-face mask - A2 size - small, Nose mask - B1 size - small, and Nose pillow mask - H1 size - small. It should be noted that the number of masks obtained in this step may only be one.

[0085] This invention provides a method for recommending personalized ventilation therapy masks by using facial scanning technology to identify the proportions of a user's facial features and to investigate the user's sleep habits. The questionnaire mainly investigates the user's daily life habits, usage habits, and sleep patterns. The questionnaire is divided into two parts. The first part filters from an existing mask library, removing unsuitable mask types. The second part scores or rates the remaining masks in the mask library using a formula. Next, a facial scanner is used to acquire the user's facial image, identifying and measuring the user's nasal wing width, lip thickness, and the vertical distance from the corner of the mouth to the eyebrow, etc. Based on the obtained data, the remaining masks are also scored or rated. The scores from the second questionnaire are compared with the facial scan results, and the one or more masks with the highest scores are recommended to the user.

[0086] In step S133, when the number of masks with large values ​​is one, the mask with large values ​​is determined to be the mask of the target specification corresponding to the target model under the target mask type.

[0087] For example, in step S131 above, a total of 3 masks may be obtained, but only one mask may be obtained. For instance, when filtering for the second user's preferred mask, only one mask may be selected, so only one mask may be selected in step S131. For example, if the mask type, model, and specification corresponding to the selected mask is "Nose Mask - B1 Model - Small Size", then "Nose Mask - B1 Model - Small Size" is determined as the target model and target specification mask under the target type, and finally, this target mask is recommended to the user.

[0088] The embodiment provided by this invention can not only filter the type of face mask, but also further refine it to the model and specifications, thus greatly improving the accuracy of the screening and improving user satisfaction.

[0089] In step S135, when there are multiple masks with large values, the multiple masks with large values ​​are sorted, and a specific number of masks are determined as the masks of the target specifications corresponding to the target model under the target mask type.

[0090] For example, when there are multiple masks selected in step S131, the masks are sorted from largest to smallest according to their scores, such as the masks with the largest scores in step S131: Nose pillow mask - H1 model - small (4.8 points), nose mask - B1 model - small (4.35 points), and full face mask - A2 model - small (4 points). A specific number of masks (e.g., the first two) are determined as the target size masks corresponding to the target models under the target mask type. That is, the nose pillow mask - H1 model - small and the nose mask - B1 model - small are recommended to the user as the final target masks.

[0091] The key to this approach is to compare the scores from the second questionnaire and the facial scan, and then analyze which mask is more suitable for the user based on which score is higher. If the second questionnaire score is higher, the second questionnaire score is used; if the facial scan score is higher, only the mask scan analysis results are used.

[0092] In another embodiment of the present invention, when the first score and the second score respectively correspond to multiple specifications of a single model or multiple specifications of multiple models of face masks, the step of determining the target specification of the target model under the target face mask type based on the first score and the second score can also be achieved by filtering the target face mask through the following steps.

[0093] In step S132, the first score and the second score of masks belonging to the same mask type, model and specification are weighted and summed to obtain multiple comprehensive scores.

[0094] For example, if there are multiple masks with the second user preference in steps S131 and S133, the first score and the second score of masks belonging to the same mask type, model, and specification are weighted and summed to obtain multiple comprehensive scores. For instance, because the scan data provides the user's facial features, this part of the data can more objectively reflect the degree of matching between the face and the mask, which is beneficial to improving the screening accuracy. The second score corresponding to the facial scan has a higher weight (e.g., 50% to 80%). The questionnaire part mainly reflects the user's personalized needs and subjective preferences, and the weight of the first score in this part is set to 20% to 50%.

[0095] The first scores for the most preferred face masks are as follows: Full-face mask - A1 size - medium - 3.85 points; Full-face mask - A2 size - small - 4 points; Nose mask - B1 size - small - 4.35 points; and Nose pillow mask - H1 size - small - 4.8 points. The second scores for the most preferred face masks are as follows: Full-face mask - A1 size - medium - 4 points; Full-face mask - A2 size - small - 3.5 points; Nose mask - B1 size - small - 3.5 points; and Nose pillow mask - H1 size - small - 3.5 points. For example, if the weight of the first score is 20% and the weight of the second score is 80%, the two scores are weighted and summed to obtain the following overall scores: Full Face Mask - A1 size - medium size: 3.97 points; Full Face Mask - A2 size - small size: 3.6 points; Nose Mask - B1 size - small size: 3.67 points; and Nose Pillow Mask - H1 size - small size: 3.76 points.

[0096] In step S134, the multiple comprehensive scores are sorted, and a specific number of masks are determined as the target specifications of the target model under the target mask type.

[0097] For example, the above multiple comprehensive scores are sorted, for instance, from highest to lowest score: Full-face mask - A1 size - medium (comprehensive score 3.97), nose pillow mask - H1 size - small (comprehensive score 3.76), nose mask - B1 size - small (comprehensive score 3.67), and full-face mask - A2 size - small (comprehensive score 3.6). Then, a specific number of these four masks (e.g., the top two ranked masks) are selected as target masks. Therefore, the full-face mask - A1 size - medium and the nose pillow mask - H1 size - small are recommended to the user.

[0098] The key to this approach is combining the scan score (secondary score) and the second questionnaire score (primary score), with the scan score taking precedence. Unlike the approaches mentioned above that simply select the highest score, this approach combines both scores, resulting in more accurate recommendations. Furthermore, it comprehensively considers both subjective and objective factors to recommend more suitable face masks.

[0099] The technical solution provided by this invention performs an initial screening of all mask types based on user survey questionnaire results, eliminating mask types that do not meet user preferences to obtain a first set of preferred mask types. Then, based on the subjective questionnaire results, all models and specifications of the selected first set of preferred mask types are scored to obtain a first score. Next, based on the user's facial scan data and the preset scores corresponding to the facial data of each specification of the first set of preferred masks, a second score corresponding to the user's scan data is obtained. Finally, by combining the first score from the subjective questionnaire and the second score corresponding to the user's facial scan data, the specific mask type, its corresponding model, and its specific specifications are determined. This technical solution considers both the user's subjective needs and each user's facial data, achieving more accurate mask recommendations and effectively improving user satisfaction.

[0100] like Figure 4 This is a structural diagram of a face mask selection system provided in the second embodiment of the present invention. The second embodiment of the present invention also provides a face mask selection system 20, comprising: a selection module 201, used to select one or more face mask types preferred by a first user from all types of face masks based on user questionnaire results. Each face mask type includes multiple models, each model includes multiple specifications, and the questionnaire results include subjective questionnaire results; a first acquisition module 202, used to score each specification of face mask corresponding to each model under each face mask type preferred by the first user based on the subjective questionnaire results, to obtain a first score for each specification of face mask corresponding to each model under each face mask type preferred by the first user; a second acquisition module 203, used to obtain a second score for each specification of face mask corresponding to each model under each face mask type preferred by the second user based on preset scores corresponding to user facial scan data and facial data of each specification of face mask preferred by the first user; and a determination module 204, used to determine the target specification of face mask corresponding to the target model under the target face mask type based on the first score and the second score.

[0101] The mask selection system provided in the second embodiment of the present invention performs the same mask selection method and achieves the same technical effects as the first embodiment described above, and will not be repeated here.

[0102] A third embodiment of the present invention also provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the mask selection method as described in any one of the present invention.

[0103] The method for selecting a face mask performed by an electronic device and the technical effects achieved by the third embodiment of the present invention are the same as those of the first embodiment described above, and will not be repeated here.

[0104] A fourth embodiment of the present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the mask selection method as described above.

[0105] The method for selecting a face mask executed by a computer-readable storage medium and the technical effects achieved in the fourth embodiment of the present invention are the same as those in the first embodiment described above, and will not be repeated here.

[0106] The fifth embodiment of the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the mask selection method as described above.

[0107] The method for selecting a face mask executed by a computer program product and the technical effects achieved in the fifth embodiment of the present invention are the same as those in the first embodiment described above, and will not be repeated here.

[0108] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0110] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0112] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0113] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0114] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0115] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0116] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for selecting a face mask, characterized in that, include: Based on the results of the user survey, select one or more types of face masks that are preferred by the first user from all types of face masks. Each type of face mask includes multiple models, and each model includes multiple specifications. The survey results include subjective survey results. Based on the results of the subjective questionnaire, scores are assigned to each model and specification of face mask corresponding to each type of face mask preferred by the first user, so as to obtain the first score of each model and specification of face mask corresponding to each type of face mask preferred by the first user. Based on the user's facial scan data and the preset scores corresponding to the facial data of each size of mask preferred by the first user, a second score is obtained for each model of each mask type preferred by the second user, corresponding to each size of mask; and, Based on the first score and the second score, determine the target specification of the mask corresponding to the target model under the target mask type.

2. The method for selecting a face mask according to claim 1, characterized in that, The step of obtaining the second score for each model of each mask under each type of mask preferred by the second user, based on the user's facial scan data and the preset score corresponding to the facial data of each size of mask preferred by the first user, includes: Based on each model of each mask type under the first user's preference, obtain the facial data of each specification of mask for each specification of mask preferred by the first user. Assign preset scores to the facial data of each size of mask preferred by the first user; and, Based on the preset score corresponding to the facial data of each specification of mask in the first user preference and the user's facial scan data, a second score is obtained for each model of each specification of mask under each mask type in the second user preference.

3. The method for selecting a face mask according to claim 2, characterized in that, The step of obtaining the second score for each model of each mask under each type of mask preferred by the second user, based on the preset score corresponding to the facial data of each specification of mask in the first user preference and the user's facial scan data, includes: The user's facial scan data is compared with the facial data of each size of mask preferred by the first user to obtain the third score corresponding to the user's facial scan data falling into the facial data of each size of mask preferred by the first user. Each model of each type corresponding to the third score is identified as the mask of the second user preference. The third score corresponding to the mask preferred by the second user is determined as the second score for each model and specification of mask under each mask type preferred by the second user.

4. The method for selecting a face mask according to claim 1, characterized in that, The step of determining the target specification of the target model under the target mask type based on the first score and the second score includes: The first score and the second score of masks belonging to the same mask type, model and specification are compared, and the mask with the larger value between the first score and the second score is selected. When the number of masks with the larger value is one, the mask with the larger value is identified as the mask of the target specification corresponding to the target model under the target mask type; or... When there are multiple masks with large values, the masks with large values ​​are sorted, and a specific number of masks are determined as the masks of the target specifications corresponding to the target model under the target mask type.

5. The method for selecting a face mask according to claim 1, characterized in that, When the first score and the second score respectively correspond to multiple specifications of a single model of face mask or multiple specifications of multiple models of face masks, The step of determining the target specification of the target model under the target mask type based on the first score and the second score further includes: The first score and the second score of masks belonging to the same mask type, model and specification are weighted and summed to obtain multiple comprehensive scores; The multiple comprehensive scores are sorted, and a specific number of masks are determined as the target specifications of the target model under the target mask type.

6. The method for selecting a face mask according to claim 1, characterized in that, in, The subjective questionnaire results include multiple pre-set questions. The step of scoring each model of each mask corresponding to each specification under each mask type preferred by the first user based on the results of the subjective questionnaire, to obtain the first score of each model of each specification of mask under each mask type preferred by the first user, includes: Based on the results of the subjective questionnaire, scores are assigned to each of the multiple preset questions from multiple evaluation dimensions to obtain the scores corresponding to the multiple preset questions under multiple evaluation dimensions. Based on the scores corresponding to multiple preset questions under the multiple evaluation dimensions, determine the average score of the multiple preset questions under each evaluation dimension; and, The first score for each specification of face mask corresponding to each model is obtained based on the average score of multiple preset questions under each evaluation dimension and the preset weight corresponding to each specification of face mask for each model.

7. The method for selecting a face mask according to claim 1, characterized in that, The survey results also include objective questionnaire results. The step of selecting one or more types of face masks with the first user preference from all types of face masks based on the user's questionnaire results includes: Based on the results of the objective questionnaire, a face mask that matches the results of the objective questionnaire is selected from all types of face masks to obtain one or more types of face masks preferred by the first user.

8. A face mask selection system, characterized in that, include: The selection module is used to select one or more mask types that the user prefers from all types of masks based on the results of the user's questionnaire. Each mask type includes multiple models, and each model includes multiple specifications. The questionnaire results include subjective questionnaire results. The first acquisition module is used to score each specification of face mask corresponding to each model under each type of face mask preferred by the first user based on the results of the subjective questionnaire, so as to obtain the first score of each specification of face mask corresponding to each model under each type of face mask preferred by the first user. The second acquisition module is used to obtain a second score for each model of each mask under each mask type preferred by the second user, based on the user's facial scan data and the preset score corresponding to the facial data of each mask type preferred by the first user; and, The determination module is used to determine the target specification of the mask corresponding to the target model under the target mask type based on the first score and the second score.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes the computer execution instructions stored in the memory to implement the mask selection method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the mask selection method as described in any one of claims 1-7.

11. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method for selecting a face mask as described in any one of claims 1-7.

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