Computing method and system for consultation, diagnostic evaluation and financial planning

Abstract

The present invention relates to a computing method and system for obtaining a treatment plan for a user. The method comprises the steps of receiving, on a computing platform, a plurality of general input data from a given user, generating a treatment identifier code from the plurality of general input data, collecting a plurality of consultation data relating to the user, scanning, on the computing platform, at least one portion of the user, and generating the treatment plan on the basis of the scan of at least one portion of the user. The present invention also relates to a computing system and platform in conjunction with the method described.

Description

Descriptive Report of the Invention Patent for "METHOD AND COMPUTATIONAL SYSTEM FOR CONSULTATION, DIAGNOSTIC EVALUATION AND FINANCIAL PLANNING".

[0001] The present invention relates to a method and computer system for supporting consultation, diagnostic assessment, and budgeting (financial planning). More specifically, it relates to a method and system in which, based on user interaction with a computer platform, a specific treatment plan is provided to the user. A device capable of implementing the proposed method is also discussed. Description of the state of the art

[0002] Treatment plans are commonly generated, and increasingly frequently, for a specific user. For example, a treatment plan may be related to a cosmetic treatment plan and / or a health treatment plan to be completed by a specific user. A user should be understood as, for example, a specific patient, healthcare professional, or any person capable of interacting with a computing platform.

[0003] There are several challenges today, resulting from the increased number of non-physician professionals authorized to perform procedures that were previously only authorized by physicians, such as aesthetic and health treatments and the creation of an appropriate and personalized treatment plan for a patient. The unbridled growth of unqualified professionals in various health areas, and of companies offering aesthetic products, including minimally invasive procedures, is putting in question the ability of regulatory bodies to provide adequate guidance and oversight of processes that occur from the very beginning. consideration of including the patient to undergo some procedure, until the end of the treatment and long-term follow-up.

[0004] For example, one of the challenges encountered in the state of the art lies in the difficulty of interaction between the medical professional or qualified health professional and the user, whether due to issues of distance, schedule, language, costs, among other factors.

[0005] In one example, a user must go to the doctor's or healthcare professional's clinic, an action that, in some situations, may not be carried out easily and simply by the user.

[0006] Furthermore, in many situations, there are difficulties for the doctor or health professional to adequately identify which is the best treatment plan to be provided for a given user, given that the diagnosis received by the user often differs according to the experience or even lack of experience of the professional who will indicate a treatment, which can lead to complications and unnatural results, that is, unsatisfactory for the user.

[0007] Such difficulties, for example, lie in identifying the exact location where a given substance should be applied, as well as the method (manner) of application. An additional challenge lies in the scarcity of information available in medical records; thus, neither the physician or qualified healthcare professional, nor the user, are aware of the history of treatment plans created for that user, especially for cosmetic procedures. Thus, the lack of organized and controlled information negatively influences the treatment to be performed as well as future treatments.

[0008] Furthermore, it is up to the doctor or qualified health professional to carry out a comprehensive and specialized consultation, carry out an evaluation and provide the costs associated with the treatment plan to be generated. In other words, the healthcare professional assumes a commercial role, thus distancing themselves from their primary role, which is to operate in the healthcare sector. This ultimately creates distortions in care and service delivery, potentially placing financial interests above the well-being and health of the patient.

[0009] The challenges encountered in the state of the art are not limited to the scope of the user and the medical professional (or healthcare professional).

[0010] These challenges also extend to companies that manufacture various products, including aesthetic products, such as injectable substances, support threads, various laser, ultrasound, radiofrequency (among others) machines, topical products, among others.

[0011] In the case of unsatisfactory results, mild to severe complications, the lack of organized and uniform control of the user's medical records can lead to conflicts between the parties involved. For example, neither the healthcare professional, the user, nor the companies often have knowledge of which specific procedure or substance was administered to a user, nor which healthcare professional was responsible for administering it. The present invention overcomes such problems, allowing, for example, greater organization and control of user-related information.

[0012] Furthermore, despite numerous training courses for healthcare professionals, cosmetic procedures, including the application of injectable substances, can be performed inappropriately, which can be detrimental to all parties involved: the user, who will receive ineffective treatment, and the medical or healthcare professional and the manufacturing company, whose reputations will be affected. The present invention will also assist in supporting educational and training of professionals involved in the process.

[0013] Therefore, manufacturing companies simply do not know how the substances they develop are being injected or even how their products or machinery are being used, either due to a lack of structured training or even a lack of adequate documentation.

[0014] The present invention overcomes these and several other problems found in the state of the art linked to various aesthetic treatments by proposing a method and computational system for consultation, diagnostic evaluation and budgeting.

[0015] Furthermore, based on the teachings of the present invention, legal support and assistance are provided to regulatory bodies that will need a structured and organized platform to promote balance and sustainable growth in the health sector, including aesthetics, a sector that presents uncontrolled exponential growth, which can cause damage, often difficult to repair, to users.

[0016] As will be better understood from the description that follows, said method and system are based on the use of a computer platform by the user, so that the use of said platform by the user can occur with or without the presence of a doctor or qualified health professional, thus, only from the direct interaction of the user with the computer platform, or with the assistance of any person able to interact with the computer platform, a suggestion of a treatment plan will be provided to the user of the platform.

[0017] Thus, with the present invention, there is no specific need for user interaction with the medical or health professional in the first stages of care, such as for example, to carrying out the consultation, diagnostic evaluation, budgeting and generation of the treatment plan, so that the medical or health professional, if desired by the user, can then be selected or suggested by the database of this system.

[0018] There are several advantages obtained from the actions and teachings of the present invention, advantages that can be absorbed by all links in the chain, whether by the user (patient), by the doctor or health professional, by companies manufacturing injectables or any product or machinery used in aesthetics, even by the various existing regulatory bodies that aim at good medical and health practice. Objectives of the Invention

[0019] The present invention aims to propose a computational method for consultation, diagnostic evaluation and financial planning to obtain a treatment plan, control organized data and provide future treatment possibilities (including artificial intelligence) linked to a given user.

[0020] One of the objectives of the present invention is that the proposed method be carried out through a computational platform, such as a cell phone, tablet, television, totem, or equivalent electronic device that can be created and that allows interaction with the user.

[0021] One of the objectives of the present invention is that the consultation, diagnostic evaluation, treatment plan and budgeting (financial planning) can be generated from the interaction between the user and the computer platform, not necessarily requiring the participation of a medical professional or health professional in these steps.

[0022] The present invention also aims to propose of a computer system for consultation, diagnostic evaluation and financial planning to generate a treatment plan linked to a specific user.

[0023] One of the objectives of the present invention also resides in the provision of a computational platform capable of carrying out the methodology described in the present invention; Brief description of the invention

[0024] A computational method for consultation, diagnostic evaluation and financial planning to obtain a treatment plan related to a user is described, the method comprising the steps of: receiving, on a computational platform, a plurality of general input data from a given user, generating a treatment identification code from the plurality of general input data, collecting a plurality of consultation data related to the user, scanning, on the computational platform, at least a portion of the user, and generating the treatment plan from the scanning of at least a portion of the user.

[0025] The present invention also describes a computational system and platform in harmony with the proposed method. Brief description of the drawings The present invention will now be described in more detail based on an example of execution represented in the drawings. The figures show: FIG. 1 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the receipt of general input data, such as identification data, detailed consultation on anamnesis, habits, personal history, medications, surgeries and previous treatments, including aesthetic ones, among other relevant information about the user's health status; FIG. 2 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the provision of aesthetic data including the areas of interest for treatment by the user; FIG. 3 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the provision of expectations of the emotional and / or social messages desired by the user; FIG. 4 - is a block representation of the methodology described in the present invention illustrating the steps for generating the final set of aesthetic data as well as the final set of emotional data; FIG. 5 - is a block representation of the methodology described in the present invention illustrating the steps for generating the final set of social data; FIG. 6 is a block representation of the methodology described in the present invention illustrating the steps for generating the difficulty index to obtain the result desired by the user. The difficulty index can be obtained, for example, from the user's age, the presence of signs of aging, the degree of severity, among other parameters to be determined, for example, after facial scanning; FIG. 7 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the horizontal scanning of the user's portion; FIG. 8 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the horizontal scanning of the user's portion; FIG. 9 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the horizontal scanning of the user's portion; FIG. 10 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the horizontal scanning of the user's face, in an oblique mode; FIG. 11 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the horizontal scanning of the user's face, in a lateral mode; FIG. 12 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the vertical scanning of the user's portion, in a frontal mode; FIG. 13 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the vertical scanning of the user's portion, in an oblique mode; FIG. 14 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the vertical scanning of the user's portion, in a lateral mode; FIG. 15 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the implementation of the step of generating a plurality of segments from the horizontal scanning of the user's face, in which Fig. 15 (a) illustrates the user's face in a frontal mode, Fig. 15 (b) illustrates the user's face in an oblique mode and Fig. 15 (c) illustrates the user's face in an oblique mode. Fig. 15 (c) illustrates the user's face in a side view; FIG. 16 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the computational platform as well as the implementation of the step of generating a plurality of segments from the vertical scanning of the user's face, in which Fig. 16 (a) illustrates the user's face in a frontal mode, Fig. 16 (b) illustrates the user's face in an oblique mode and Fig. 16 (c) illustrates the user's face in a lateral mode; FIG. 17 - is a representation of the step of correlating the scan of the user portion with the set of virtual emotional and social data; FIG. 18 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of comparing the user's portion in a static state and in a dynamic state, including various facial expressions such as smile, surprise, disappointment, etc.; FIG. 19 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of comparing the user portion in a static state and in a dynamic state; FIG. 20 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of segmenting the user portion into two halves; FIG. 21 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of forming the first representation and the second representation of the user; FIG. 22 - illustrates an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the scanning step of the first representation and the second. second user representation; FIG. 23 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the vertical scanning step of a second representation of the user; FIG. 24 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of representing an unfavorable indication to the user; FIG. 25 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the vertical scanning step of a usual portion of the user; FIG. 26 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of representing a negative indication to the user; FIG. 27 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user, in a dynamic state; FIG. 28 - is a representation of one of the steps that integrates the methodology described in the present invention; FIG. 29 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a frontal (Fig. 29 (a)), oblique (Fig. 29 (b)) and lateral (Fig. 29 (c)) manner; FIG. 30 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a frontal (Fig. 30 (a)), oblique (Fig. 30 (b)) and lateral (Fig. 30 (c)) manner; FIG. 31 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a frontal (Fig. 31 (a)), oblique (Fig. 31 (b)) and lateral (Fig. 31 (c)) manner; FIG. 32 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a frontal (Fig. 32 (a)), oblique (Fig. 32 (b)) and lateral (Fig. 32 (c)) manner; FIG. 33 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a static state and in a dynamic state, in which Fig. 33 (a) represents the static and dynamic state, Fig. 33 (b) represents the segmentation of the face into a plurality of quadrants and Fig. 33 (c) represents the indication of an aesthetic marker; FIG. 34 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a static state and in a dynamic state, in which Fig. 34 (a) represents the static and dynamic state, Fig. 34 (b) represents the segmentation of the face into a plurality of quadrants and Fig. 34 (c) represents the indication of an aesthetic marker; FIG. 35 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of scanning a portion of the user in a static state and in a dynamic state, in which Fig. 35 (a) represents a first expression and Fig. 35 (b) represents a second expression; FIG. 36 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of segmenting the user's face into a plurality of micro segments MS; FIG. 37 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating a exemplification of a model considered ideal, in which Fig. 37 (a) illustrates the segmentation of the model considered ideal into a plurality of quadrants and Fig. 37 (b) illustrates the assignment of an ideal index to each of these quadrants; FIG. 38 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of comparing a portion considered ideal with a current portion of the user; FIG. 39 - is an additional representation of one of the steps that integrates the methodology described in the present invention, illustrating the step of comparing a portion considered ideal with a current portion of the user, in which said portions are segmented into a plurality of quadrants; FIG. 40 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the exemplary step of indicating the monitoring, consideration and treatment portions based on the ATP (Aging Trigger Points) concept; FIG. 41 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the exemplary step of indicating at least one treatment code, so that, in this case, they refer to codes for treating dynamic expressions; FIG. 42 - is a representation of one of the steps that integrates the methodology described in the present invention, illustrating the exemplary step of indicating at least one application dose; FIG. 43 is a representation of an application seal that incorporates the teachings of the present invention, wherein Fig. 43(a) illustrates a generic application seal and Fig. 43(b) illustrates the application seal comprising a plurality of information, including of, the application site (treatment code), the type of product, the layer to be injected, the way the product is distributed and the quantity to be injected; FIG. 44 - is a representation of one of the steps that integrates the methodology proposed in the present invention, showing the generation of a treatment plan in the form of a table for a given session; FIG. 45 - illustrates the correlation stage between the treatment plan and the application seals, for a given application session; FIG. 46 - illustrates the correlation stage between the treatment plan and the application seals, for a given application session; FIG. 47 - illustrates the correlation stage between the treatment plan and the application seals, for a given application session; FIG. 48 - illustrates the correlation stage between the treatment plan and the application seals, for a given application session; FIG. 49 - illustrates one of the steps that integrate the methodology proposed in the present invention, representing the generation of an application chain for a given user; FIG. 50 - is a representation of one of the steps that integrates the methodology described in the present invention, representing the arrangement of reference lines for evaluating the treatment performed; FIG. 51 - is an exemplary illustration of an electronic device capable of absorbing the teachings of the present invention; FIG. 52 - illustrates an example of body treatment codes; FIG. 53 - illustrates a second example of body treatment codes; FIG. 54 - illustrates a third example of body treatment codes; FIG. 55 - illustrates a fourth example of body treatment codes; FIG. 56 - is an example of a graphic representation generated by artificial intelligence of a professional in the aesthetics field. FIG. 57 - is an example of a graphical representation generated by artificial intelligence, illustrating a multidisciplinary graphical representation. FIG. 58 - is an example of one of the steps that integrates the methodology described in the present invention, representing the simulation of an aging process; FIG. 59 - is an example of one of the steps that integrates the methodology described in the present invention, representing the simulation of the illustration of possible results through the implementation of a treatment plan. FIG. 60 - is an additional example of one of the steps that integrates the methodology described in the present invention, representing the simulation of the illustration of possible results through the implementation of a treatment plan; FIG. 61 - is an additional example of one of the steps that integrates the methodology described in the present invention, representing the simulation of the illustration of possible results through the implementation of a treatment plan; FIG. 62 - is a representation of a user who can make use of the teachings of the present invention, in which said user makes use of an augmented reality device; FIG. 63 - is an example of a first instruction perceivable through the use of an augmented reality device; FIG. 64 - is an example of a marking made on the patient who will receive a certain application; FIG. 65 - is an example of a second instruction perceivable through the use of an augmented reality device; FIG. 66 - is an example of a marking made on the patient who will receive a certain application; FIG. 67 - is a representation of a third instruction perceivable through the use of an augmented reality device; FIG. 68 - is a representation of a fourth instruction perceivable through the use of an augmented reality device; FIG. 69 - is a representation of a fifth instruction perceivable through the use of an augmented reality device; FIG. 70 - is a representation of a sixth instruction perceivable through the use of an augmented reality device; FIG. 71 - is an additional representation of a sixth instruction perceivable through the use of an augmented reality device; FIG. 72 - is an example of a graphic indication perceptible through the use of an augmented reality device; Figure 73 - illustrates a representation of a user's interaction modality with the computing platform; Figure 74 - illustrates a representation of an additional mode of user interaction with the computing platform and also through the graphical representation generated by artificial intelligence, in which a case study is presented to the user; Figure 75 - illustrates a representation of an additional mode of user interaction with the computing platform, illustrating the association of an application seal with a case study; Figure 76 - illustrates a representation of an additional mode of user interaction with the computing platform, illustrating the arrangement of a set of instructions in a manner superimposed on the case study; Figure 77 - illustrates a representation of an additional mode of user interaction with the computing platform, illustrating the arrangement of a set of instructions in a manner superimposed on the case study; Figure 78 - illustrates a representation of an additional mode of user interaction with the computing platform, illustrating the generation of a test seal by the user. Detailed description of the figures

[0026] The present invention initially describes a method and computational system for consultation, diagnostic assessment, and financial planning (budgeting) related to the generation of a treatment plan for a given user. More specifically, the proposed method will provide a treatment plan to the user based on the user's interaction with a computational platform 30.

[0027] By computing platform 30, we can understand any electronic device capable of establishing an internet connection, such as a computer, cell phone, tablet, smartwatch, television, totem, among others. FIG. 51 is an example of a electronic device capable of being understood as a computing platform 30. It is also noteworthy that the teachings of the present invention do not necessarily require the computing platform 30 to be connected to the internet, so that the interaction with the user can be done offline and subsequently uploaded to the platform once the connection is reestablished or started.

[0028] It is proposed that said computing platform 30 comprises a block capable of receiving at least one specific input data from the user and inserting said input data into the methodology proposed in the present invention, thus, the computing platform must comprise an input block 31, in which the input block 31 can be understood, for example, as a keyboard, a camera, a combination of these, or any other means capable of receiving data (information) from the user and inserting such data (information) from the user into the methodology proposed in the present invention.

[0029] The methodology proposed in the present invention must then be accessed by the user through their interaction with the aforementioned computing platform. The manner in which the user accesses the computing platform does not represent the essential aspect of the invention, so any form of access would be fully valid, such as access via login, password, and / or facial biometrics.

[0030] For example, in one embodiment, the computing platform 30 could be accessed by the user through an electronic address entered into an internet browser, alternatively, or additionally, through the user's access to a particular application installed on an electronic device, such as on a television, cell phone or tablet.

[0031] User access to the computer platform can be confirmed by completing a prior registration and providing a login and password. Therefore, when accessing the computer platform, national, an account linked to the user will be created. It is therefore understood that the methodology proposed in the present invention comprises the step of creating an account linked to the user, so that a user code could be generated.

[0032] The method proposed in the present invention proposes the step of receiving, on the computational platform, a plurality of general input data from a given user.

[0033] Thus, when accessing the computing platform, the user will be prompted to provide a plurality of general input data, which general data must be stored, for example, in the memory of the computing platform and / or the methodology proposed in the present invention. It is thus understood that the computing platform comprises a memory that stores a set of instructions, in which said set of instructions can be executed by a processor. In one embodiment, said memory could be located in a cloud environment or could be configured as the computing platform's own memory.

[0034] General input data should be understood as the provision of data that allows the identification of the user's name, as well as the identification of basic user information, such as nationality, gender, and date of birth. Typically, the provision of information contained in the user's passport, driver's license, or national identity card constitutes data suitable for configuring general input data.

[0035] Said general input data may be entered into the computing platform by any means, whether by typing, scanning documents, uploading documents, voice, or a combination thereof. The manner in which the general input data will be entered into the computing platform does not represent the essential aspect of the present invention, so that any form insertion would be fully valid.

[0036] Furthermore, it is also proposed that the computational platform motivate the user, through a generating block, to indicate consent with a term of adhesion, which may be linked to practices related to data protection, health practices, or any practice linked to a specific country or region.

[0037] Thus, FIG. 1 illustrates a representation of the computing platform (of its screen) in which the steps of receiving general input data A and consent to the adhesion term B are illustrated.

[0038] Thus, once the user has provided general input data and established consent to the terms of adhesion, the computational platform assesses whether such data has been properly inputted and, thus, the sequence of the methodology proposed in the present invention is achieved.

[0039] Still taking as reference the illustration in FIG. 1, the methodology proposed in the present invention comprises the step of generating a treatment identification code C from the plurality of general input data. Thus, it is proposed that the computational platform will generate a specific treatment code linked to that user, in which said code can be understood as an identification code for entry into the database system to then proceed with the proposed subsequent steps, such as consultation, diagnostic evaluation, and creation of a treatment plan suggestion.

[0040] This treatment code can be randomly generated by the computing platform and can be composed of, for example, numbers, letters, or a combination of these. Any form of representation of the treatment code can be used. The way the treatment code is displayed in the figure in question should not be considered as a limiting feature of the present invention.

[0041] It should be noted that the aforementioned treatment identifier code should be understood as a code that associates a given user with consultation, diagnostic evaluation, and financial planning data. Thus, a given user may include multiple treatment identifier subcodes associated with the user, as the user may undergo a series of treatments throughout their life.

[0042] Thus, if a user obtains a treatment plan today, a specific treatment code will be generated and associated with the user. If the same user obtains a new treatment plan at a future date, a new treatment code will be generated and associated with the user. Thus, it is understood that each treatment code is associated with a specific date.

[0043] It is therefore understood that the same user may be associated with a series of processing identification subcodes.

[0044] Furthermore, and taking as reference the illustration in FIG. 1, it can be seen that the treatment identification code generated for the user is code NH 073.562.017.

[0045] Once the treatment identification code has been generated, the methodology described here also proposes the step of collecting a plurality of consultation data related to the user, a step identified with reference D, as can be seen from FIG. 1.

[0046] By consultation data, we should understand data (information) commonly found in medical records (or health records), for example, and not limited to, consultation data can be understood as the following data: (i) whether the user has any clinical condition (disease), (ii) whether the user has completed their vaccination schedule, (iii) whether the user has recently had a vaccination. any dental procedure, (iv) if the user has any allergies, (v) if the user is taking any medication, (vi) if the user has ever undergone any aesthetic procedure, such as a facial aesthetic procedure, (vii) if the user has ever received an application of botulinum toxin, (viii) if the user has ever received an application of permanent fillers, (ix) if the user has ever received an application of hyaluronic acid, (x) if the user has ever received biostimulators (xi) if the user has ever received any type of treatment, (xii) if the user has ever had any adverse reaction to any type of medication, treatment, and / or application and / or (xiii) anamnesis data.

[0047] The query data discussed in the previous paragraph should not be considered limiting, so that other query data could be addressed and integrate the methodology proposed in the present invention. Thus, the description provided is intended to allow an understanding of the query data.

[0048] In a valid embodiment of the present invention, information provided by the user to the computing platform 30 could be collected through the user's interaction with a graphical representation of a medical professional, such as a graphical representation generated by artificial intelligence.

[0049] Thus, this graphical representation should be understood as a representation, for example, of the medical professional's face, including the medical professional's voice. Thus, all interaction between the user and the computing platform will be conducted by this type of "avatar" (a graphical representation of the doctor generated by artificial intelligence). Furthermore, this graphical representation should be understood as a representation of the user's face, capable of expression, that is, capable of movement, and that also includes the voice of the doctor or healthcare professional.

[0050] Thus, it is understood that the voice of the aforementioned representation Graphical display can be selected, for example, according to the user's preferences for a particular language.

[0051] Furthermore, the proposal to use the graphical representation generated by artificial intelligence becomes beneficial as it provides greater confidence to the user in the process of interacting with the computational platform, since the user will literally see (observe, see) the face of a doctor or health professional, endowed with expressions, and hear their voice, thus acting as a mentor in the process of generating the treatment plan.

[0052] In an additional embodiment, the user's interaction with the computing platform could be further performed through the user's interaction with a plurality of additional graphical representations 200, 300, 400, 500, 600, 700, 800, 900 and 1000.

[0053] With reference to FIG. 57, said additional graphical representations 200, 300, 400, 500, 600, 700, 800, 900, 1000 and 1100 also referred to as multidisciplinary representations, aim to assist both the professional and the user during their interaction with the computational platform.

[0054] Thus, said multidisciplinary representations 200, 300, 400, 500, 600, 700, 800, 900, 1000, and 1100, as well as the representation of physician 100, must also be generated through artificial intelligence. Furthermore, multidisciplinary representations 200, 300, 400, 500, 600, 700, 800, 900, 1000, and 1100 are configured as representations of professionals from different fields of expertise, areas of expertise that assist both the professional and the user during interaction with the computational platform.

[0055] Thus, FIG. 57 is an exemplary representation of the multidisciplinary graphical representations 200, 300, 400, 500, 600, 700, 800, 900, 1000, and 1100 as well as the graphical representation of the medical professional 100.

[0056] Thus, a first multidisciplinary graphical representation 200 may refer, for example, to the graphical representation generated by artificial intelligence of a biomedical professional, who is responsible for, during the user's interaction with the computational platform, assisting with the evaluation and monitoring of patients.

[0057] A second multidisciplinary graphical representation 300 may refer, for example, to the graphical representation generated by artificial intelligence of a teacher, who is responsible for, for example, during the user's interaction with the computer platform, keeping both the user and the professional updated with the most recent scientific reports in the area.

[0058] A third multidisciplinary graphical representation 400 may refer, for example, to the graphical representation generated by artificial intelligence of a nurse, who is responsible for, during the interaction of the user / professional with the computer platform, providing information on pre- and post-treatment care.

[0059] Additionally, a fourth multidisciplinary graphic representation 500 may refer, for example, to a pharmacist, who is responsible, for example, for sharing important details about the care and storage of injectable products.

[0060] A fifth multidisciplinary graphic representation 600 may refer, for example, to the graphic representation of an accounting professional, who may provide guidance on fees, taxes and related topics.

[0061] A sixth multidisciplinary graphic representation 700 may refer, for example, to the graphic representation generated by artificial intelligence of a marketing professional, who is responsible for providing tips on advertising strategies to the manager of an aesthetic clinic, for example.

[0062] Still, a seventh multidisciplinary graphic representation 800 may refer, for example, to a product consultant, who is responsible for presenting, to both the user and the professional, a portfolio of products that can be used to generate the treatment plan.

[0063] An eighth multidisciplinary graphic representation 900 may refer, for example, to a business manager, who may be responsible for offering guidance on clinic management.

[0064] A ninth multidisciplinary graphic representation 1000 may refer, for example, to a digital influencer, who may help, for example, in promoting the work carried out by a professional on social media.

[0065] Furthermore, a tenth multidisciplinary graphical representation 1100 may refer, for example, to the artificial intelligence-generated graphical representation of a lawyer, who is responsible for assisting with legal matters, such as consent forms and patient documentation.

[0066] It should be noted that the multidisciplinary graphic representations mentioned above should not refer to limiting characteristics of the present invention, so that the representation of other professions / positions would be fully acceptable.

[0067] Furthermore, the multidisciplinary graphical representations 200, 300, 400, 500, 600, 700, 800, 900, 1000, and 1100 can be configured according to the user's and / or professional's country of residence. For example, if the user absorbing the teachings of the present invention resides in Japan, the multidisciplinary graphical representation 1100 of the lawyer will assist both the user and the professional with legal issues specific to that location (Japan).

[0068] Furthermore, it is proposed that each multidisciplinary graphic representation be given a name, a name that contains the letters Al or IA in its designation, as an allusion to artificial intelligence, and that said multidisciplinary graphic representation is presented to the user and / or professional, for example, through a video.

[0069] It should be noted that all the characteristics already mentioned for the graphic representation of the medical professional 100 are also valid for the multidisciplinary graphic representations 200, 300, 400, 500, 600, 700, 800, 900, 1000 and 1100.

[0070] Thus, FIG. 1 is a non-limiting representation of the computational platform 30, illustrating some of the steps that integrate the methodology proposed in the present invention. For example, the step of receiving the general input data A, accepting the consent form B, generating the treatment identifier code C and collecting the consultation data D is illustrated.

[0071] Query data D can be collected from any database associated with the computing platform, such as from a memory capable of storing query data from multiple users. It is thus understood that query data is filled in by the user and stored in said memory.

[0072] Once the consultation data has been collected, the methodology described in the present invention also proposes the step of evaluating whether there is, in the consultation data related to the user, any restrictive data. By restrictive data, we should understand data (information) that contraindicates the user from obtaining the treatment plan.

[0073] For example, restrictive data can be understood as data indicating whether the user has recently undergone a dental procedure, or data indicating that the user has an allergy, or data indicating that the user is receiving a certain medication that contraindicates the use of injectables, or data indicating that the user had a certain reaction to a previously performed procedure.

[0074] Furthermore, the present invention also proposes carrying out the step of associating the restrictive data with the identification code of the treatment of that user, as well as associating the restrictive data with the user code.

[0075] Thus, suppose that a user experienced a specific adverse reaction in a treatment plan previously undertaken. Therefore, it is proposed that the occurrence of this adverse reaction (restrictive data) be associated with that user's treatment identifier code, as well as with the user's identifier code. Thus, if the user generates a new treatment subcode in the future, it will be possible to know that, in the past, a restrictive data occurred related to that user. Restrictive data do not contraindicate treatment, but they will serve as a warning for future clinical evaluation by the physician or qualified healthcare professional selected to perform the procedure.

[0076] Thus, the present invention comprises the step of evaluating whether, in the query data related to the user, there is restrictive data, as well as evaluating whether there is restrictive data related to the user.

[0077] If restrictive data is detected, it is proposed to carry out the step of issuing a representation perceptible to the user, for example, on the screen of the computing platform 30. Said representation can be configured as text, an image, an audible representation, as well as a combination of any of these.

[0078] The purpose of issuing the representation perceptible to the user is to issue an alert to the user regarding the existence of the restrictive data, so that the existence of the restrictive data should not necessarily be understood as an impediment to the sequence of the proposed methodology.

[0079] Following the description of the teachings of the present invention, there is the step of obtaining at least a first con- along with aesthetic data from the user based on an impulsive representation of the patient.

[0080] Thus, it is proposed that the computational platform should motivate the user to provide an initial set of aesthetic data. More specifically, the provision of an initial set of aesthetic data should occur through an impulsive representation of the patient. Impulsive representation can also be understood as a subjective representation, as will be described below.

[0081] By the first set of aesthetic data, it should be understood as a series of aesthetic data that a given user is interested in treating, more specifically, the first set of aesthetic data should be understood as the regions / parts of the face and / or body that the user is interested in correcting or improving through the treatment plan.

[0082] By impulsive (subjective) user representation, we mean that the user should impulsively provide the first set of aesthetic data to the computer platform 30. More specifically, the user may simply input the first set of aesthetic data into the computer platform. To this end, the computer platform may, for example, display a text box (input block 31) that prompts the user to enter the first set of aesthetic data. The system may also provide a list of areas, regions, or parts of the face and / or body so that the user is aware of potential treatment areas.

[0083] Furthermore, the impulsive representation of the user can be understood as the act of activating an optical capture element (such as a camera) of the computational platform and, through the capture of a video of the user, the user will be motivated to provide the first set of aesthetic data.

[0084] Thus, the computing platform 30 will prompt the user to provide the first set of aesthetic data by activating the optical capture element, recording a video of the user, and providing a field for the user to input the first set of aesthetic data, for example. It is further proposed that the first set of aesthetic data be provided by the user while the user visualizes themselves in the video captured by the camera.

[0085] In an analogy, the user's impulsive representation can be understood as the act of the user looking in a mirror, so that the mirror, in this case, can also refer to the capture of the user's video through the computational platform.

[0086] Thus, it is understood that the step of obtaining at least a first set of aesthetic data from the user based on an impulsive representation of the user also comprises the step of activating an optical capture element of the computing platform and capturing a video of the user, thus motivating the user to provide the first set of aesthetic data. More specifically, the user evaluates the video and provides the first set of aesthetic data.

[0087] Additionally, the methodology described in the present invention further comprises the step of obtaining at least a second set of aesthetic user data from a graphical representation of the user. By graphical representation, we mean a photo of the user.

[0088] Thus, the methodology proposed in the present invention encourages the user, through the computing platform, to evaluate their own photo and input the second set of aesthetic data based on the photo evaluation. The user's photo evaluation can occur by uploading a photo of the user to the computing platform or by capturing a photo of the user using the optical capture element of the computing platform itself 30.

[0089] It is thus understood that the step of obtaining at least a second set of aesthetic data from a graphical representation of the user also includes the step of obtaining the second set of aesthetic data through the user's analysis of their own photo. More specifically, the user evaluates their photo and provides the second set of aesthetic data. Graphical representation can also be understood as an objective representation of the user, as the user evaluates their photo and objectively provides the second set of aesthetic data.

[0090] FIG. 2 is an illustration of the computational platform representing the previously discussed steps for obtaining the first and second aesthetic data sets.

[0091] As previously described in FIG. 2, this assessment can be performed using a mirror, photo, camera, or any other equivalent method. The system will identify whether there is consistency between the user's intended request when looking in the mirror and the photo taken during the consultation. The system is also configured to assist the user in prioritizing treatment areas, highlight inconsistencies, and serve as an educational tool for the user's subjective self-assessment.

[0092] Taking FIG. 2 as a reference, the first set of aesthetic data obtained from the impulsive representation can be considered as the following aesthetic data: 1. Upper eyelids; 2. Forehead lines; 3. Nasolabial folds. The second set of aesthetic data obtained from the graphical representation of the user can be understood as 1. Upper eyelids; 2. Nasolabial folds; and 3. Temple.

[0093] Furthermore, it is worth noting that the aesthetic data initially provided by the user (or provided first in the list of aesthetic data sets) can be understood as the most relevant aesthetic data, that is, the aesthetic data that the user has the greatest interest / desire to process. In the case of the representation in FIG. 2, the aesthetic data related to the upper eyelid can be understood as the most relevant data, both for impulsive (subjective) feedback and for graphical (objective) feedback.

[0094] Once the first and second sets of aesthetic data have been obtained, the methodology described here proposes the step of evaluating, in a comparator module, whether there is consistency between each of the aesthetic data from the first set of aesthetic data and the second set of aesthetic data.

[0095] Thus, in a comparator block, understood as a processor, microprocessor or any element capable of performing a comparison between data, it will be evaluated whether there is consistency between the aesthetic data of the first set and the aesthetic data of the second set.

[0096] More specifically, we will evaluate whether the aesthetic data in the first aesthetic dataset is the same as the aesthetic data in the second aesthetic dataset. Even more specifically, we will evaluate whether the aesthetic data provided by the user in the impulsive feedback (impulsive representation) is the same as the aesthetic data provided by the user in the graphical feedback (graphical representation). We will also evaluate whether the order provided for the aesthetic data is the same, considering the first and second aesthetic datasets.

[0097] In the exemplary illustration in FIG. 2, the comparator block, when evaluating the first aesthetic data of the impulsive representation (mirror) and the first aesthetic data of the graphical representation (photo), will detect a consistency, since such aesthetic data are the same (upper eyelids).

[0098] When comparing the second aesthetic datum of the impulsive representation with the second aesthetic datum of the graphic representation, an inconsistency will be detected, since there is data relating to forehead lines for the impulsive return and data relating to nasolabial folds for the graphic representation. Similarly, an inconsistency will also be detected when comparing the third aesthetic datum of the impulsive representation with the third aesthetic datum of the graphic representation.

[0099] In the representation in FIG. 2, the comparison indicates the existence of inconsistencies; in this case, the proposed step is to issue a representation perceptible to the user. More specifically, the computing platform should inform / alert the user that an inconsistency has been detected, since the aesthetic data provided by the user in the impulsive return does not match the aesthetic data provided by the user from the graphical representation. The indication of an inconsistency is illustrated in FIG. 2, starting from step E.

[0100] Furthermore, if an inconsistency occurs, the user should be encouraged, through the computing platform, to enter a final set of aesthetic data. The final set of aesthetic data should be understood as the aesthetic data that the user actually wishes to process. More specifically, the computing platform identified an inconsistency between the first set of aesthetic data and the second set of aesthetic data, and so the user was informed of this inconsistency.

[0101] Thus, the user, aware of the detected inconsistency, must inform the computational platform which aesthetic data should actually be considered; that is, the user must inform the final set of aesthetic data. If consistency is not achieved, the system will establish the information collected by photo analysis as a final option because it is less subjective.

[0102] Said user-perceivable representation may be configured as a text, video, audio, color representation, or a combination thereof. It should be noted that the manner in which the representation will be perceivable to the user is not the essential aspect of the present invention.

[0103] If a consistency is detected from the comparator block, that is, if there is a consistency between the first set of aesthetic data and the second set of aesthetic data, it is proposed that the user also receives a perceptible representation indicating that said consistency was detected and, additionally, it is also proposed to carry out the step of transforming the first set of aesthetic data and the second set of aesthetic data into a final set of aesthetic data.

[0104] Thus, based on the previously discussed steps, it follows that the methodology proposed in the present invention, through the computational platform, motivates (provokes) the user to inform which aesthetic data should be addressed in the treatment plan. More specifically, by obtaining aesthetic data through impulsive (subjective) and graphical (objective) representation, as described above, the methodology intensifies the provocation to the user, thus aiming to assess whether the user is fully certain and convinced of which aesthetic data should be considered in the treatment plan.

[0105] In this sense, it often happens that the user appears to be fully convinced that a certain portion of their body and / or face (such as an aesthetic feature) requires aesthetic treatment. However, when performing said aesthetic treatment on the aesthetic feature in question, the user's dissatisfaction with that particular aesthetic feature persists. In other words, the user appears to have full conviction that the treatment of that aesthetic data would be beneficial, however, after the treatment is carried out, the user's dissatisfaction remains.

[0106] This is one of the reasons why it's important to encourage users to provide aesthetic data through different representations, such as impulsive and graphic representations, as previously described. This makes the treatment plan more accurate.

[0107] Aiming to further increase the assertiveness of the treatment plan to be provided to the user, the methodology described in the present invention also proposes the step of obtaining a first set of emotional (and / or social) data (messages) from the user from the first set of aesthetic data and also obtaining a second set of emotional (and / or social) data from the user from the second set of aesthetic data.

[0108] More specifically, the first and second sets of aesthetic data refer to specific portions of the face and / or body that the user wishes to treat. In the case of the representation in FIG. 2, these portions are indicated as the eyelids, forehead, nasolabial region (nose / mouth), and temple. In other words, such aesthetic data should be understood as anatomical data, indicating specific regions of the user's face.

[0109] Emotional and / or social data / messages seek a broader motivation from the user than in relation to aesthetic data, that is, if when informing the aesthetic data the user indicated a specific portion of the face that the user wants to treat, when informing the emotional data / messages the user will provide the reason why the user wants to treat that specific aesthetic data.

[0110] More specifically, the user must indicate the reason why led him to choose that particular aesthetic data for treatment, that is, the user should inform why the user wants to treat that particular aesthetic data.

[0111] Thus, and referring now to the exemplary representation of FIG. 3, it follows that the first set of emotional data provided by the user refers to the following emotional data: (i) more attractive appearance, (ii) less tired appearance, (iii) more defined appearance (enhancement of contours).

[0112] Similarly, the second set of emotional data / messages provided by the user refers to the following emotional data: (i) more attractive, (ii) less tired, (iii) contour enhancement.

[0113] This means the user wants to treat the upper eyelid, forehead lines, and nasolabial folds to make them more attractive, less tired, and more defined. In other words, at this stage of the proposed methodology, a correlation occurs between the emotional data / messages set and the impulsive and graphical analysis, which was not previously observed with aesthetic data.

[0114] However, treating only the aesthetic data (areas / regions of the face and / or body) that the user indicates they wish to treat, such as the upper eyelids to become more attractive, the nasolabial folds to appear less tired, and the temples to enhance facial contours, will not necessarily achieve the objectives of the emotional data / messages, objectives that would require a broader facial and / or body treatment. Thus, the methodology and system described in the present invention could indicate other areas / regions for treatment in order to achieve the user's desires.

[0115] Additionally, and as proposed when obtaining the aesthetic data set, the stage of evaluating, in the comparator module, whether there is consistency between each of the emotional data in the first emotional data set and each of the emotional data in the second emotional data set.

[0116] Taking the example in FIG. 3 as a basis, it can be seen that a consistency was detected, since emotional data 1 to 3 of the first set of emotional data are the same emotional data 1 to 3 of the second set of emotional data.

[0117] Thus, once consistency has been detected, a perceptible representation is provided to the user, as indicated in step E illustrated in FIG. 3. Furthermore, once consistency has been detected, the step of transforming the first set of emotional data and the second set of emotional data into a final set of emotional data is also proposed.

[0118] Alternatively, if no consistency is detected, we also propose encouraging the user, through the computer platform, to enter the final set of emotional data. This will alert the user, through a perceptible representation, to the detected inconsistency and subsequently encourage them to provide the final set of emotional data. Unfavorable or negative messages will be prioritized for processing.

[0119] Thus, based on the previously described description and illustrations in FIGS. 2 and 3, and also taking the illustration in FIG. 4 as a basis, a final set of aesthetic data and a final set of emotional data will be obtained. It is proposed that the final set of aesthetic data and the final set of emotional data be stored on the computational platform so that they can be considered for future generation of the treatment plan. The diagnostic evaluation to be performed by the system will assist in prioritizing the areas and messages to be treated, so that the evaluation The system's actions may differ from those indicated by the user, as the user's assessment may distort their own image. For example, requesting excessive treatments that may worsen rather than improve their appearance. The user will be alerted to this possibility.

[0120] In addition to emotional data, the computational method will also enable the stage of obtaining, from a socializing block, a plurality of positive (favorable) social data linked to the user and a plurality of negative (unfavorable) social data linked to the user's appearance.

[0121] Positive social data refers to the appearance a user would like to achieve, based on a social aspect. For example, positive social data can be understood as: confident, caring, and friendly. In this case, such positive social data could have been reported if the user were a nurse; therefore, the user would like to have a more confident, caring, and friendly appearance.

[0122] The proposed socialization block comprises eight positive and eight negative social data points, so the user must provide a certain amount of positive and negative social data to continue the methodology. For example, when analyzing the graphic data (photo), the user will provide negative social data about their appearance that they would like to be corrected or improved and determine positive social data that they would like to convey with their appearance after the treatment.

[0123] For example, positive social characteristics can be considered as: appearance: trustworthy, confident, determined, friendly, kind, active, cultured, and optimistic. Negative social characteristics can be considered as: appearance: unreliable, insecure, fragile, antisocial, indifferent, discouraged, inexperienced, and pessimistic.

[0124] Once the positive and negative social data have been obtained, it is further proposed to carry out the step of consolidating the plurality of positive social data and the plurality of negative social data into a final set of social data, as seen in FIG. 5.

[0125] Thus, based on the illustrations in FIGS. 3 to 6, the output of the described methodology will be the final set of aesthetic data, the final set of emotional data, and the final set of social data. This data will later be used to analyze the feasibility of delivering the desired result. The treatment plan will prioritize addressing the negative emotional messages related to the user's appearance.

[0126] Additionally, and still referring to FIG. 6, the methodology and system described in the present invention further comprise the step of generating a difficulty index from at least the evaluation of the final set of aesthetic data, the final set of emotional data, and the final set of social data. More specifically, the difficulty index can be understood as a score that indicates, to the user and the applicant, the difficulty existing in applying the treatment plan that is being generated based on the final set of aesthetic, emotional, and social data.

[0127] It should be noted that, to generate the difficulty index, one must also consider at least the content of the user's general input data, such as their age. Thus, in a hypothetical situation, a user with an older age or significant asymmetries tends to have a difficulty index with a higher score generated.

[0128] It is worth noting that any data previously provided by the user can be considered to generate the difficulty index, such as, for example, query data. Furthermore, it is worth noting that, preferably, but not limited to, the difficulty index should be generated after scanning the user's face.

[0129] It is proposed that the difficulty index be displayed to the user through the computing platform. Thus, if the computing platform is understood as a computer, tablet, cell phone, or television, the difficulty index will be displayed on the screen of said computing platform.

[0130] The difficulty index can be understood as a number, such as a number that starts at 0 and goes up to 100, so that a difficulty index that has a maximum value of 100 indicates that the difficulty in implementing that treatment plan is maximum.

[0131] Alternatively, or additionally, the difficulty index can be configured as a text and color representation, so that, in this case, the difficulty index can be represented by the arrangement of the texts "LOW", "MEDIUM", and "HIGH". Furthermore, such texts can be arranged on the computer platform screen in certain colors; for example, the "LOW" difficulty index could be displayed in green, the "MEDIUM" difficulty index could be displayed in yellow, and the "HIGH" difficulty index could be displayed in red.

[0132] Any form of representation and generation of the difficulty index would be acceptable, such as a representation in video, text, animation, colors, as well as a combination of these.

[0133] It is proposed that the difficulty index be generated from a scan of the user, as further indicated in FIG. 6. It is thus understood that the methodology proposed in the present invention comprises the step of scanning (or any other form of graphic or digital analysis, such as the analysis of photos and / or videos), on the computational platform, at least a portion of the user. Per portion of the user, can be understood, in a non-limiting way, as the user's face.

[0134] Thus, the computer platform will scan the user's portion. To do this, input block 31 of the computer platform must be activated, as well as the platform's camera.

[0135] The step of scanning at least a portion of the user through the computing platform also comprises the step of scanning said portion of the user horizontally and vertically, and also considering a frontal portion, an oblique portion and a profile portion of the user.

[0136] FIG. 7 is a representation of the computing platform indicating the horizontal scanning step of the user's face, in which, in FIG. 7, the horizontal scanning line is indicated with the numerical reference 10. Thus, the horizontal scanning line 10 will travel the entire height of the user's face at least once. FIGS. 8 and 9 illustrate the movement of the horizontal scanning line 10 across the user's face. In one embodiment, it is proposed that the user's face be segmented into a plurality of quadrants, and as the scanning occurs, a certain index (value) is assigned to each of the quadrants of the plurality of quadrants.

[0137] Thus, it is proposed that the horizontal scanning of the user be performed considering a frontal portion of the user (FIG. 7), an oblique portion (FIG. 10), as well as a profile portion of the user (FIG. 11). The scanning can be performed using graphic data (photo) at rest and in various expressions. Video capture can also be considered for dynamic user evaluation.

[0138] Similarly, in addition to scanning through the line of horizontal scanning 10, the methodology described proposes that vertical scanning of the user will also be carried out, that is, scanning through a vertical scanning line 11.

[0139] Thus, the vertical scan 11 of the user must be performed in frontal, oblique, and profile views, as illustrated in FIGS. 12, 13, and 14, respectively. Similarly, the user's face can be segmented into a plurality of quadrants and then a certain index (value) can be assigned to the quadrants as the scan occurs.

[0140] Additionally, in addition to the scanning as previously described and illustrated in FIGS. 7 to 14, the step of scanning the user portion further comprises the step of segmenting the user portion into a plurality of segments. Thus, the computational platform will generate a plurality of slices in the user portion from the horizontal and vertical scanning.

[0141] Thus, and now referring to FIG. 15, the computational platform will segment the user's portion into a plurality of segments and from the scanning of the frontal, oblique and profile portion. Thus, FIG. 15 shows the segments generated from the vertical scanning line 11 for the scanning of the frontal, oblique and lateral portion, as shown in Figures 15 (a), (b) and (c), respectively.

[0142] Similarly, the computational platform will generate the plurality of segments also from scanning through the horizontal scanning line 10, as illustrated in FIG. 16. Thus, there are segments for scanning the frontal, oblique and lateral portion, as shown in Figures 16 (a), 16 (b) and 16 (c).

[0143] The methodology described in the present invention further comprises the step of correlating the scan of the user portion with at least one of a plurality of positive social data virtual, a plurality of virtual negative social data and a set of virtual emotional data linked to the user.

[0144] By virtual data, we should understand data generated by the computing platform itself, and not provided by the user.

[0145] For example, in the description referring to FIG. 3, it was described that the emotional data indicated in the figure were provided by the user, that is, they are desires expressed by the user himself.

[0146] Virtual emotional data should be understood as emotional data evaluated (generated) by the computing platform itself. That is, the computing platform will, by scanning the user's face, indicate which emotional data should be considered for that user. In other words, the computing platform will, by scanning the user's face, assess that user's needs, such as looking less tired, less sad, less angry, or having less sagging skin, etc.

[0147] Therefore, virtual data should be understood as data (indications) generated by the computing platform itself from scanning the user's face.

[0148] Taking as reference the illustration in FIG. 17, it can be understood that the step of correlating the scanning of the user portion with a set of virtual emotional data of the user further comprises the step of scanning a portion of the user and determining the set of virtual emotional data linked to the user.

[0149] Thus, in FIG. 17, there is a scan of the user's face, such as the scan through the horizontal scanning line 10 and the subsequent determination of the virtual emotional data set. More specifically, the determination of the virtual emotional data set indicates which emotional data should be considered in the treatment plan to be generated for that user. river.

[0150] Thus, for each virtual emotional / social data, an alert indication will be generated for priority correction of unfavorable emotional and social messages to be considered in the treatment plan.

[0151] Thus, it is understood that the computational platform will comprise a set of virtual emotional / social data previously stored in its memory, so that, for each of these data, and from the scanning of the user's face, a correction indication must be generated.

[0152] In one embodiment of the present invention, at least the following virtual emotional data sets must be stored on the computing platform: "appear less tired," "appear less sad," "appear less angry," and "appear less flabby," among others. Thus, for each of these data points, an indication must be generated, thus alerting the user to the need for treatment.

[0153] Thus, FIG. 17 shows the scanning step of the user's face as well as the indication, by the computer platform, of a suggestion (alert indication) that the user in question should have a less tired, less sad, less angry and less sagging appearance.

[0154] Thus, the system suggests that the patient should have a less tired, less sad, less angry, and less sagging appearance, so that, as can be seen in FIG. 17, in this exemplary representation, the computational platform generated an alert indication for all virtual emotional data considered. It is noteworthy that the form of illustration and representation of the alert indication as shown in FIG. 17 should only be considered as an exemplary representation, that is, it does not seeing it result in any limitation to the scope of protection of the present invention.

[0155] Having generated alert signals from the virtual emotional data set, it is proposed, by way of example, that a priority list be generated by the computing platform for the virtual emotional data considered. In this embodiment, said priority list could include the following virtual emotional data: appear less tired, appear less sad, appear less angry, and appear less flabby. As described above, for each of the virtual emotional data considered, an alert signal should be issued by the methodology and system described in the present invention.

[0156] Continuing with the description of the methodology proposed in the present invention, the computational method for obtaining a treatment plan related to a user further comprises the step of performing, through the computational platform, a dynamic scan of the user, in which the step of performing a dynamic scan of the user further comprises the step of comparing portions of the user in a static state and in a dynamic state.

[0157] In this way, the computing platform, through its processing unit, will scan a portion of the user in two different states, a first state being understood as a static state and a second state being understood as a dynamic state.

[0158] Thus, taking FIG. 18 as a reference, the user's face is scanned in a static state X and in a dynamic state Y, and both scans are compared to generate an aesthetic signal that can assume a treatment state and a non-treatment state. In FIG. 18, the aesthetic signal is generated by motivating the user to smile. Thus, the method- The technology and system described in the present invention determine whether, during various expressions (dynamic states), the user experiences an improvement (upgrade) or worsening (downgrade) in overall appearance, or whether equivalence is maintained on a pre-established scale. For example, said pre-established scale may be a scale represented by an index ranging from 0 to 10, with, for example, index 0 representing the worst possible aesthetic condition and index 10 representing the ideal aesthetic condition for age, gender, ethnicity, among other factors. Said index could be assigned, for example, by segmenting the face into a plurality of quadrants.

[0159] More specifically, the computational platform compares the user's portion in the static state X and the dynamic state Y and determines whether there has been an aesthetic improvement (non-priority treatment state), an aesthetic worsening (treatment state) or whether equivalence has been maintained (state to be considered in the treatment, but not being a priority state).

[0160] If the aesthetic flag assumes a treatment state (or a state to be considered in the treatment), it is also proposed to carry out the step of generating at least one treatment code to be considered in the user's treatment plan.

[0161] To generate the aesthetic beacon, it is proposed that when scanning the user's portion in the static state X, a static index will be generated by the computing platform. Similarly, when scanning the user's portion in the dynamic state Y, a dynamic index will be generated by the computing platform. In short, the static index and the dynamic index can be understood as values, numbers, that represent the states of the dynamic and static indexes.

[0162] Thus, once the aforementioned static and dynamic indices have been generated, a comparison is made between them and it is then assessed whether there is an aesthetically positive variation (upgrade), an aesthetically negative variation (upgrade), or a negative variation (upgrade). negative (downgrade) or if an equivalence was maintained. This comparison can be performed globally, that is, for the entire user's face, or it can be performed by segments (by quadrants) of the user's face.

[0163] Thus, if an aesthetically negative variation (downgrade) is detected, the aesthetic flag must be assigned the treatment status, and, consequently, if an aesthetically positive variation (upgrade) is detected, the aesthetic flag must be assigned the treatment non-priority status.

[0164] For example, and based on the illustration in FIG. 19, consider that user X's static scan generated a static index value of 5, while user Y's dynamic scan generated a dynamic index value of 4. Thus, the comparison indicates a downgrade, that is, an aesthetically negative variation. In this case, the aesthetic flag is assigned a treatment status. If a loss of comparative numerical value is noted, the treatment indication is termed 'correction,' while if the numerical value is maintained or improved, the treatment indication is designated as prevention or beautification of the area / region / message in question.

[0165] In one embodiment, and as will be further described below, the comparison between the static state X and the dynamic state Y could be performed by segmenting the user's face into a plurality of quadrants. Thus, the user's face should be segmented into a plurality of quadrants, for both the static state X and the dynamic state Y.

[0166] Thus, one can assign indices (values) to each of these quadrants in the static state X (or to a set of quadrants) and then compare it with its respective quadrant (or with the respective set of quadrants) in the dynamic state. In this way, from the comparison between the indexes, it can be determined whether an aesthetically positive, negative or equivalent variation occurred.

[0167] Referring further to the illustration of FIG. 20, the methodology proposed in the present invention further comprises the step of mirroring at least a portion of the user and comparing a first mirroring of the user with a second mirroring of the user.

[0168] More specifically, it is proposed that the user portion, in this case, their face, be vertically segmented into two halves, that is, a left half ME and a right half MD, as illustrated in FIG. 20. Subsequently, the step of forming a first representation of the user from the left half ME and forming a second representation of the user from the right half MD must be performed.

[0169] In other words, the user's face must be formed from two left halves ME and the user's face from two right halves MD. To do this, the left and right halves must be mirrored so that the correct face formation is possible.

[0170] Thus, FIG. 21 illustrates the first and second representations of the user, in which there is the first representation FR of the face formed by two right halves MD (also referred to as 2 x MD) as well as the second representation SR of the face formed by two left halves ME (also referred to as 2 x ME).

[0171] Subsequently, and now referring to FIG. 22, the step of scanning the first representation FR is performed as well as scanning the second representation SR and identifying which representation is aesthetically more favorable (if any), thus determining a final representation.

[0172] In other words, from the scan of the first If you choose between the first FR representation and the second SR representation, you can choose one of these representations, so that the chosen representation will be the most aesthetically pleasing. If both the first FR representation and the second SR representation are discarded, you can continue with the user's current representation, that is, the representation formed by their left and right halves. In this case, the user's face can be segmented into a plurality of quadrants, as previously described.

[0173] If one of the first FR representation and the second SR representation are chosen, said representation can be used as a benchmark, that is, a standard, such as a portion of the user considered ideal or suitable for the user in question.

[0174] The scanning step of the first FR representation and the second SR representation of the user aims to assess whether there is symmetry of the user's face based on these representations. Thus, the first FR representation is initially compared with the second SR representation, and then it is determined which representation illustrates the user's face in a more symmetrical way. To this end, it is proposed to perform a horizontal scan of each of these representations, as illustrated in FIG. 22.

[0175] In the example illustrated in FIG. 22, the second SR representation (formed by the two left halves) was excluded, so it is proposed to evaluate the first FR representation (formed by two right halves) from a vertical scan, as illustrated in FIG. 23. The objective in performing the vertical scan of the second SR representation is to evaluate whether there is a favorable or unfavorable indication in relation to the user's real image.

[0176] Thus, after vertical scanning, as shown in FIG. 23, the user will be provided, through the computer platform, with information on whether there is some side of the face, when analyzed in mirroring, shows a significant improvement compared to the real face. In the example illustrated in FIG. 23, and also referring to FIG. 24, there is an unfavorable indication, that is, no improvement was observed in the analyzed representation. Thus, since both the representation formed by the two left halves ME (2 x ME) and that formed by the two right halves MD (2 x MD) were disregarded, the real representation of the user must be evaluated, that is, that formed by their left face and their right face.

[0177] Thus, FIG. 25 represents a vertical scan of the user's usual UR representation, aiming to assess whether there is a favorable indication (there is symmetry) or an unfavorable indication (there is no symmetry) in the representation considered. Based on the representation in FIG. 26, the computational platform indicates an unfavorable indication, that is, there is no symmetry in the user's face. In such an assessment, and as for any step related to scanning the user's face, the face could be segmented into a plurality of quadrants, and indices (values) could be assigned to each of these quadrants.

[0178] In this example, since both the 2 x ME and 2 x MD representations had already been considered unfavorable to serve as models, this fact indicates a tendency for the technical difficulty of the procedure to increase, thus affecting the difficulty index. If one of the user's sides (either 2 x ME or 2 x MD) had been considered superior to the real side, then the side with the best aesthetic appearance could serve as a guide (benchmark), that is, a model considered ideal.

[0179] In this case, the unfavorable indication related to the symmetry of the user's face provides an alert to the user (and the medical or health professional) related to the treatment plan that is being implemented. consideration.

[0180] It is noteworthy that the asymmetry assessment must be performed, for the representation under consideration (in this case, the usual representation), both statically and dynamically, that is, considering that the user is both at rest and, for example, smiling, as shown in FIGS. 27 and 28. Obviously, other expressions, besides smiling, could be considered. It is noteworthy that in the examples illustrated in FIGS. 26 to 28, asymmetry was detected both at rest and in a dynamic state, which tends to increase the level of difficulty associated with treatment.

[0181] Subsequently, the user can be scanned based on the next hierarchies, for example, such as the H2, H3, H4 and H5 hierarchies discussed in US patent 11,602,303.

[0182] More specifically, scanning from the H2 hierarchy will consider the following evaluation parameters: ideal, favorable, acceptable, unfavorable.

[0183] Thus, the user portion will be scanned based on the H2 hierarchy and, for each scan performed, a specific evaluation parameter will be reported through the computational platform.

[0184] Thus, and taking FIG. 29 as a reference, it is proposed that, for the upper third of H2, the user's portion should be scanned frontally (Fig. 29 (a)), obliquely (Fig. 29 (b)), and laterally (Fig. 29 (c)), and thus return an evaluation parameter. In an example, the evaluation parameter returned after scanning the upper third of H2 is the "favorable" parameter. By treating a favorable parameter, if it is the user's desire, we are promoting 'beautification'.

[0185] Similarly, the same steps are performed for the median third of H2, thus scanning the user's portion frontally (Fig. 30 (a)), obliquely (Fig. 30 (b)), and laterally (Fig. 30 (c)), thus returning an evaluation parameter. In one example, the evaluation parameter returned after scanning the median third of H2 is the "unfavorable" parameter. By treating an unfavorable parameter, we are promoting a 'correction' of that facial third.

[0186] Similarly, the same steps are performed for the lower third of H2, thus scanning the user portion frontally (Fig. 31 (a)), obliquely (Fig. 31 (b)) and laterally (Fig. 31 (c)) and thus returning an evaluation parameter. In one example, the evaluation parameter returned after scanning the lower third of H2 is the “unfavorable” parameter.

[0187] Similarly, the same steps are performed for the user's neck, considering the H2 hierarchy, thus scanning the user's neck frontally (Fig. 32 (a)), obliquely (Fig. 32 (b)), and laterally (Fig. 32 (c)), and thus returning an evaluation parameter. In an example, the evaluation parameter returned after scanning the user's neck is the "acceptable" parameter. By treating an 'acceptable' parameter, we are promoting the 'prevention' of the considered region.

[0188] To obtain the evaluation parameters, the user's face can be segmented into a plurality of quadrants and thus assigned indexes to each of the quadrants, these indexes will correspond to the evaluation parameters. By way of example only, the ideal evaluation parameter can be assigned a maximum index (value), the unfavorable evaluation parameter can be assigned a minimum index (value), and the other parameters (favorable and acceptable) can be assigned intermediate values, between maximum and minimum.

[0189] Subsequently, it is proposed to scan the user's face from the H3 hierarchy, so that said scan should consider the following evaluation parameters: aesthetically positive variation (upgrade), aesthetically negative variation (downgrade) and aesthetically equivalent variation (equivalent).

[0190] Thus, at this stage, portions of the user are compared in a static state and in a dynamic state, so that, by static state, it can be understood as the user's face at rest and, by dynamic state, it can be understood as the movement of the user's face.

[0191] Thus, and taking as reference the illustration in FIG. 33, the portion of the user in the static state and in the dynamic state is compared, in which, in this case, the dynamic state is understood as the act of the user frowning.

[0192] More specifically, it is proposed that, through the computational platform, the user's face be segmented into a plurality of quadrants Q, as illustrated in Fig. 33 (b) and, for each of these quadrants, a static index (for the resting state) and a dynamic index (for the animated state) be assigned. Thus, the computational platform must compare each static index and each dynamic index for each of the quadrants and thus assess whether an aesthetically positive variation (upgrade), an aesthetically negative variation (downgrade) or an aesthetically equivalent variation has occurred.

[0193] It is understood that the occurrence of an aesthetically negative variation indicates the generation of an aesthetic flag that will receive a treatment status. The occurrence of an aesthetically positive variation indicates the generation of an aesthetic flag that receives a non-treatment priority status, but if the treatment is Once achieved, the objective becomes preventive or beautifying. Similarly, the occurrence of an aesthetically equivalent variation indicates the generation of an aesthetic flag that receives a non-treatment priority status, but treatment with preventive or beautifying objectives is also considered, if desired by the user. If the user wishes to treat a region, area (quadrants, or set of quadrants) for which a no-treatment aesthetic flag was initially assigned, said aesthetic flag must be updated, thus assigning it a treatment aesthetic flag.

[0194] Thus, when it is detected that an aesthetically negative variation has occurred, an aesthetic marker 20 can be displayed on the computational platform in the respective quadrant that originated said aesthetically negative variation, thus providing an indication to the user that that point of the face will be the target of treatment. It is worth noting that an example of the aesthetic marker 20 is illustrated in Fig. 33 (c), in which it is, for example, represented as a square.

[0195] This form of representation of the aesthetic marker should not be considered a limiting form of representation, so any other form of representation would be fully acceptable. Furthermore, although FIG. 33(c) illustrates only one aesthetic marker, it is noteworthy that a plurality of aesthetic markers could be illustrated on the computational platform.

[0196] Thus, the steps discussed above and illustrated in FIG. 33 should be performed for certain dynamic user states and, for example, for each of the referenced segments of the H3 hierarchy. Therefore, since FIG. 33 illustrates the dynamic state understood as the act of frowning, it is proposed that the same methodology be performed for the dynamic states of raising the eyebrow and smiling, among others.

[0197] Thus, for each of these dynamic states, the user's face must be segmented into the quadrants already mentioned and, from these, the static and dynamic indices must be assigned and then the appropriate comparison carried out, thus resulting in the evaluation of whether there is an aesthetically positive, negative, or equivalent variation.

[0198] It is worth noting that the comparison between each of the quadrants of the static index and the dynamic index can be carried out individually, that is, each quadrant of the static index will be compared with its respective quadrant of the dynamic index, or it can be carried out in groups, grouping a certain number of quadrants of the static index and comparing them with their respective equivalent quadrants of the dynamic index.

[0199] Thus, at the end of the comparison between the static state and the dynamic state, data will be obtained that indicates the existence of an aesthetically positive, negative, or equivalent variation. For example, the dynamic state of frowning resulted in an aesthetically negative variation, while the dynamic state of raising one's eyebrow also resulted in an aesthetically negative variation, while the dynamic state of smiling resulted in an aesthetically equivalent variation.

[0200] Obtaining information regarding aesthetically positive, negative, or equivalent variation may consider the number of quadrants related to the user's face. For example, if a greater number of quadrants resulting in a positive variation has been observed (the quadrant's index (value) increased from the static state to the dynamic state), the data linked to the aesthetically positive variation will then be reported, i.e., indicating that there is no treatment priority.

[0201] On the other hand, if a greater number of quadrants were observed that resulted in a negative variation (index ce (value) of the quadrant decreased from the static state to the dynamic state), the data linked to the aesthetically negative variation will then be reported, thus indicating that there is a priority need for aesthetic treatment.

[0202] Similarly, if it has been observed that the number of quadrants whose index increased and decreased was the same, an aesthetically equivalent variation will be reported, thus indicating that there is no treatment priority.

[0203] It is also proposed that the same procedure performed above be also performed for the perioral region of the H3 hierarchy, that is, the region close to the user's lips.

[0204] Thus, in reference to FIG. 34, there is a comparison of the user's portion for the static state and for the dynamic state of the perioral region, in which it is proposed that the dynamic state be understood as, for example, the act of the user smiling (or any other expression), as illustrated in Fig. 34 (a). Thus, and in reference to Figs. 34 (b) and (c), there is the segmentation of the user's face into the plurality of quadrants Q as well as the indication of the aesthetic marker, as previously commented.

[0205] In an example, the comparison between the static state and the dynamic state considering the act of the user smiling could result in an aesthetically equivalent variation.

[0206] Similarly, it is proposed that other dynamic variations of the user be considered for the perioral region, such as the act of the user moving the mouth and lips simulating a kiss (Fig. 35 (a) as well as moving the mouth and lips in order to display the pout (pouting), as illustrated in Fig. 35 (b).

[0207] Thus, in an example, the dynamic state of simulating a kiss could result in an aesthetically equivalent variation, while the dynamic state of displaying the lip could result in a aesthetically negative variation, thus indicating the need to consider that region (for example, indicated by a certain quadrant, or groups of quadrants) in the treatment plan.

[0208] It is proposed that the comparison between the static and dynamic states be performed using user photos, which could, for example, be uploaded by the user to the computing platform or captured directly by the computing platform, for example, from a camera. Expression analysis through video would also be possible, as this analysis is considered more sophisticated and complex, making the analysis of graphic data through photos faster and more feasible.

[0209] Thus, the computer platform can motivate the user to take a certain photo, for example, by displaying a message to the user asking them to take a photo moving their mouth to simulate a kiss, a pout, or even moving their forehead and eyebrows.

[0210] Furthermore, the static index previously mentioned could, for example, be initially assigned by the computing platform and related to a specific ethnicity, age group or gender of the user.

[0211] Subsequently, having carried out the evaluation for the H3 hierarchy, the next hierarchy of the face can now be evaluated, this one referenced as H4.

[0212] The H4 hierarchy has already been presented, for example, in the corresponding patent US 11,602,303 and refers to the segmentation of the face into a plurality of subunits. It is thus understood that the step of scanning at least a portion of the user further comprises the step of segmenting the portion of the user into a plurality of micro segments MS, as illustrated in FIG. 36.

[0213] Therefore, at this stage, at least one portion must be compared. tion of the user (such as one of the segments of the plurality of MS micro segments) with a portion considered as 'ideal'.

[0214] The portion considered ideal can be understood as a benchmark for comparison, so that said portion considered ideal can be suggested by the computer platform itself, taking into account the user's ethnicity, age group and gender identity, or it can even be provided by the user of the computer platform itself.

[0215] Thus, if provided by the computational platform, said platform should, for example, suggest 10 models considered ideal, so that the user can select the model they like best. In one embodiment, each of the models suggested to the user may also contain a respective difficulty level—that is, the difficulty the user would have in achieving the aesthetic state of the model suggested by the computational platform, starting from their current aesthetic state.

[0216] In one embodiment, such ideal models (portions considered ideal) can be understood as people, such as celebrities, to be suggested to the user. Thus, the user has the possibility of choosing the ideal model linked to a specific person, thus indicating that the user wishes, after completing the treatment plan, to be aesthetically similar to that specific chosen person.

[0217] In equally valid modalities, the ideal models to be suggested to the user can be suggested based on age models, that is, the user can choose a model that refers to an “ideal 35-year-old model”, said model then comprising aesthetic data considered ideal for a 35-year-old person. Furthermore, ideal models can also be suggested based on a certain ethnicity, for example, thus suggesting a “ideal role model for a Caucasian person”, or even an “ideal role model for a 45-year-old Caucasian person”.

[0218] In an equally valid modality, the user can be motivated, through the computational platform, to freely indicate which ideal model the user wishes to select.

[0219] Thus, it is understood that a given model considered ideal will comprise a plurality of ideal aesthetic data, such as a plurality of ideal aesthetic data for each of the quadrants (or set of quadrants) of the user's face, as indicated in FIG. 37. Thus, each of the aesthetic data considered ideal for each of the quadrants may comprise a certain ideal index, such as an ideal value (for example, numbering from 0 to 10), so that said numbering will be used as a basis for comparison with the user's actual data, thus indicating which, and how many, aesthetic interventions that user needs to perform to get as close as possible to the model considered ideal, or even indicate the impossibility of achieving that goal desired by the user.

[0220] It is thus understood that the user portion (such as a given micro-segment MS of the user's face obtained from a plurality of segments) comprises a plurality of real aesthetic data; for example, each of the segments (quadrants) of the user's face may comprise a certain real aesthetic data. For example, the real aesthetic data can be understood as indexes (such as a number from 0 to 10) for each of the quadrants of the user's face, so that such indexes (real aesthetic data) will then be compared with the respective ideal aesthetic data, thus returning whether there is a need for aesthetic treatment in that region.

[0221] In one modality, the aesthetic data considered ideal (and consequently the ideal model) can be previously stored stored in a memory of the computational platform, alternatively, or additionally, the aesthetic data considered ideal can be obtained from clinical tests, more specifically, from data arranged in clinical tests as well as from data found in the literature, it is then possible to generate the values ​​of the indexes for each of the ideal aesthetic data and then insert them into the computational platform.

[0222] Additionally, or alternatively, the ideal model can be generated by the computing platform itself, for example, through artificial intelligence, in which the computing platform can be motivated, for example, to draw the face of a model considered ideal and corresponding to a 50-year-old person. Furthermore, the artificial intelligence can be motivated to draw an ideal model of the user themselves, for example, from a younger photo of the user.

[0223] Thus, when evaluating the user's photo, artificial intelligence can redraw the photo considering an aesthetically appropriate user expression, for example, without the effects of time, stress and poor diet.

[0224] Furthermore, and as previously mentioned, the model considered ideal (and consequently the ideal aesthetic data) can be previously stored in the computational platform and obtained from a plurality of models considered ideal.

[0225] Thus, and with reference to FIGS. 38 and 39, each of the MS microsegments must be compared with its respective ideal MS microsegment. To perform such a comparison, and as already described, the MS microsegment can be divided into a plurality of Q quadrants, thus assigning a respective index to each of the quadrants (such as a number from 0 to 10). Thus, and as previously described and with reference to the H3 hierarchy, the indexes considered ideal are compared to the respective real indexes.

[0226] Subsequently, it is proposed that the computational platform returns which aesthetic interferences that particular user should be subjected to so that he or she becomes aesthetically close (or similar) to the model considered ideal for that particular segment.

[0227] Thus, and with reference to at least FIGS. 38 and 39, each of the values ​​(indices) of the quadrants (or set of quadrants) considered ideal is compared with the respective real quadrants. Thus, in an example, if there is a difference between the ideal index and the real index, this fact will indicate that the specific region comprising the said quadrant should be the target of an aesthetic treatment.

[0228] Thus, when carrying out the commented evaluation, the computational platform can, for example, return unsightly parameters that must be treated so that the real user becomes aesthetically similar (or close) to the model considered as ideal.

[0229] In one embodiment, such unsightly parameters may, for example, be identified as: excessively high eyebrow, excess skin on the upper eyelid, small eye shape, low lateral canthus, prominent lacrimal groove, loss of cheek volume.

[0230] It is therefore proposed that the methodology discussed above be carried out for each of the MS micro segments of the plurality of segments illustrated in FIG. 38. Furthermore, the comparison with a model considered ideal can be carried out both in a static state and in a dynamic state.

[0231] By comparing the model considered ideal with the user's current model, as well as by scanning the user's face, the computational platform can then return por- monitoring user portions, consideration portions, and treatment portions.

[0232] This defines measures to be taken for that user, based on a comparison with their ideal model.

[0233] Thus, monitoring portions can be understood as portions (areas, regions, quadrants) of the user that deserve to be monitored over time. In other words, they may indicate portions that currently do not require aesthetic treatment, but that may eventually, over a period of time (monitoring period), require aesthetic intervention. Thus, such portions can be stored in the database of the computational platform linked to that particular user, so that monitoring is automatically performed by the computational platform.

[0234] In one embodiment, it is proposed that the user will receive a notification, such as an audible, textual, graphic signal, as well as a combination of these, when the period of time, referred to as the final monitoring period, is approaching or has already expired.

[0235] Portions of consideration can be understood as portions that are slightly far from the portions considered ideal, that is, they are portions that are currently in an aesthetic state considered acceptable, thus, the computational platform can suggest that the user consider such portions in the treatment plan to be generated, with the aim of beautification or prevention.

[0236] Finally, by treatment portions, we should understand those portions (regions, areas, segments, quadrants, groups of quadrants) that are too far from the respective portion considered ideal, thus indicating that there is a need for said portion is treated so that the user achieves an aesthetic close to (or similar to) the aesthetic of the model considered ideal according to age group, ethnicity and gender identity.

[0237] In one embodiment, the assessment that a portion will be defined as a monitoring, consideration, or treatment portion may be taken from an aesthetic variation index Aest, so that said aesthetic variation index may be understood as the difference between the ideal aesthetic index and the actual aesthetic index, that is:

[0238] Aest = |lestideai - lesteai | (expression I)

[0239] Thus, the aesthetic variation index A es t indicates how far the actual aesthetic index (lesteai) is from the ideal aesthetic index (lestideai). Thus, ranges of magnitude can be determined, indicating, for example, three ranges of magnitude that refer to the monitoring, consideration, and treatment portions, respectively.

[0240] In one embodiment, the ideal aesthetic index can be assigned a total value of 10, thus, for each of the quadrants of the segment under analysis, the value of 10 can be assigned, reference is made, for example, to Fig. 37 (b).

[0241] Thus, values ​​for the aesthetic variation index A es t that are in the range from 0 to 1 should return, for example, that that particular portion falls within a monitoring portion, thus indicating that the real aesthetic index assumed a value equal to 10 or equal to 9.

[0242] Already values ​​for the aesthetic variation index A es t that are in the range of 2 to 4 should return, for example, that that particular portion falls within a portion of consideration, thus indicating that the real aesthetic index assumed values ​​of 8, 7 or 6.

[0243] Already values ​​for the aesthetic variation index A es t that are in the range of 5 to 10 indicate that the portion under consideration (current / real portion) is too far from the portion considered ideal, so that said portion must then be classified as a treatment portion, thus indicating that the real index assumes values ​​of 5, 4, 3, 2, 1 or 0.

[0244] The value ranges described here should be considered as examples only. Furthermore, the ideal aesthetic index does not necessarily have to assume a total value of 10, so any value can be assigned to the index in question (for this reason, it is suggested that the expression I be considered as a modulus). In any case, it is suggested that the values ​​for the ideal and actual aesthetic index be positive.

[0245] In short, the further away the actual aesthetic index is from the ideal aesthetic index, the greater the indication of the need for aesthetic treatment in the portion of the user in question.

[0246] In one embodiment, signaling to the user which portions should be understood as monitoring, consideration and treatment portions can be done by indicating the quadrants of the user's face that gave rise to the respective signaling.

[0247] Thus, it is possible, for example, to superimpose the quadrants in question on the user's face, delimiting, for example, in green, the quadrants that indicate the monitoring portions, in yellow the quadrants that indicate consideration portions and in red the quadrants that indicate treatment portions.

[0248] Additionally, or alternatively, the indication to the user regarding the monitoring, consideration and treatment portions can be carried out as illustrated in FIG. 40, thus being carried out from the so-called ATP Aging Trigger Points, points already commented on, for example, in patent US 11,602,303.

[0249] Thus, in an embodiment as illustrated in FIG. 40, the ATPs related to the treatment portions could be highlighted to the user in red. Furthermore, it may optionally be chosen not to show the user the ATPs related to the monitoring and consideration portions, or, alternatively, the monitoring portions could be indicated in green and the consideration portions could be indicated in yellow.

[0250] Thus, once the portions that will be the target of aesthetic treatment have been defined, the aesthetic signal is generated, more specifically, the aesthetic signal is indicated in a state of treatment.

[0251] In this sense, the aesthetic signal can be understood as data (information) generated by the computational platform that indicates that an aesthetic treatment should be performed on that specific portion of the user. The aesthetic signal can be generated from any scanning method of the user's face described in the present invention.

[0252] Thus, having defined the portions that will be the target of an aesthetic treatment, that is, having defined the treatment portions, the methodology described in the present invention also proposes the step of obtaining and generating at least one treatment code from the aesthetic flag, so that, by aesthetic flag, it should be understood as any data that refers to the computational platform the need to carry out an aesthetic treatment.

[0253] A treatment code should be understood as a code that indicates to the physician or qualified healthcare professional at least the site that should receive the aesthetic treatment. Furthermore, this treatment code may also indicate to the healthcare professional not only the treatment site but also provide instructions related to the application of a specific substance, so that said instructions may be related to the application dose, the application instrument, the way of distributing the product, the depth of application, the application angle, among others.

[0254] In a valid embodiment, such application codes may be understood as the MD Codes and / or MDDyna codes addressed in US patent 11,602,303. In any case, it is emphasized that, considering the teachings of the present invention, such treatment codes should be understood as any treatment code (i.e., a textual, numerical, graphical representation, as well as a combination thereof) that indicates to the healthcare professional at least the application site of a substance.

[0255] In an exemplary embodiment, such TC treatment codes may refer to treatment codes indicating the application site on a user's face. In an equally valid embodiment, such TC treatment codes may refer to body treatment codes, such as the indication of FIGS. 52-55.

[0256] Thus, the present invention further comprises the step of displaying the TC treatment codes on a portion of the user, as illustrated by way of example in FIG. 41. It is noteworthy that such TC treatment codes must also be displayed on the screen of the computing platform.

[0257] Additionally, the proposed step is to display at least one application dose related to the TC treatment codes. Thus, for each treatment code obtained, the computational platform must display a respective treatment dose, as illustrated, by way of example, in FIG. 42. Thus, a total of doses to be applied and related to the user's treatment plan must also be displayed.

[0258] In a valid embodiment of the present invention, and from the generated TC treatment codes, the step of correlate the generated TC treatment codes with the final set of aesthetic, emotional and social data previously obtained and already commented on.

[0259] Thus, the computer platform evaluates and informs the user whether the TC treatment codes obtained correspond to the regions and areas previously indicated by the user as being desirable regions and areas for treatment.

[0260] It is worth noting that, to generate CT treatment codes, it is suggested that priority be given to scanning the user's face and / or body and thus detecting areas, regions and quadrants that require priority aesthetic intervention.

[0261] Having identified and generated the TC treatment codes with the respective application doses, and having displayed them through the computational platform, the present invention also proposes the step of generating at least one application seal linked to the user.

[0262] The application seal S1, S2, S3, S4...SN can be understood as data (information) capable of being read by a computer and which includes a plurality of information related to the generated treatment plan. Thus, the application seal S1, S2, S3, S4...SN is understood as, for example, a file that can be read, processed, stored, transmitted, and received through computational means. Furthermore, it is understood that the application seal 51, S2, S3, S4...SN is capable of storing a plurality of information that can subsequently be read and processed by computational means. In a valid embodiment, the application seals S1, 52, S3, S4...SN could be read and processed through an augmented reality and / or virtual reality device, such as glasses equipped with features linked to augmented reality and or virtual reality.

[0263] Thus, the application seal S1, S2, S3, S4...SN is configured as a structure that directs (orients) application parameters for a given substance and considers a specific treatment code. Thus, the application seal could, for example, be sent from the computer platform to the personal computer of a physician or qualified healthcare professional, so that, upon receiving the application seal S1, S2, S3, S4...SN, the physician will have all the necessary information to administer the substance.

[0264] Furthermore, the application seal S1, S2, S3, S4...SN could, for example, be sent from the computational platform to an automated applicator of a given substance, such as an applicator robot (mechanical arm). Thus, upon receiving the application seal S1, S2, S3, S4...SN, the automated applicator could read and process it, thus automatically applying the substance to the user. It is understood that, upon receiving the application seal S1, S2, S3, S4...SN, the automated applicator's mechanical arm will move, thus transitioning from a resting (stationary) state to a moving state.

[0265] Considering the teachings of the present invention, and still referring to the illustration of FIG. 43, it is proposed that the application seal has stored at least the following information (data): a TC treatment code data, an application product data, an application layer data, an application device data, an application mode data, an active number (dose) data.

[0266] Furthermore, and even though the application seal S1, S2, S3, S4...SN should be understood as a file capable of being read by a computer, it is proposed that said application seal also include a graphical arrangement of your information that allows correct reading and identification to the professional who will receive the application seal.

[0267] Thus, the application seal is also understood as a way of graphically providing information (instructions) related to the application of the substance to a specific user.

[0268] Thus, and based on the previously described description, it is understood that the application seal is configured as at least one of: a computer-readable application seal and a user-readable application seal.

[0269] FIG. 43 illustrates a preferred graphical representation of the proposed structure for the application seal S1. Preferably, the application seal S1 comprises a square-shaped structure, in which a set of three pieces of information are arranged in a first half of the application seal and an additional set of three pieces of information are arranged in the second half of the application seal. It is thus understood that the application seal is segmented into at least a first portion and a second portion, in which each portion comprises the same amount of data.

[0270] Thus, and in reference to Figs. 43 (a) and (b), it can be seen that the application seal comprises a treatment code data TC, in this case, Ck1, thus indicating the application site to the medical professional or to the professional who makes use of the teachings of the present invention. Furthermore, it can be seen that the application seal S1 indicates the application product, in this case, referenced as a product A.

[0271] The S1 application seal also indicates the application layer, so this indication can be made through a graphic element, such as a figure. In this case, the figure of a skull indicates to the professional that the application should occur on the patient's bony plane (periosteum / supraperiosteum).

[0272] Similarly, the application seal also indicates the application device through a graphic element, so that, in reference to the illustration in Fig. 43(b), the professional is told that the application should be carried out with a specific instrument, such as a needle.

[0273] Furthermore, the application method is also indicated through a graphic element, in this case, a circle is represented, thus allowing the professional to understand that the application should occur in aliquots.

[0274] Finally, the data relating to the active number (volume / dose / units) indicates to the professional the application dose, in this case, consisting of three applications of 0.1 ml each.

[0275] It should be noted that the graphic elements and treatment codes that should make up the application seals may be those already known in the state of the art, for example, found in the literature and related to MD Codes and MD Dyna Codes.

[0276] Having generated the application stamps S1, S2, S3, S4...SN, the present invention then proposes the step of generating the treatment plan from said application stamps S1, S2, S3, S4...SN.

[0277] In one embodiment, the treatment plan could be generated directly by the computing platform, thus comprising at least data regarding the number of sessions, cost data for the generated treatment plan, and information regarding the person responsible for implementing the treatment plan (whether a medical professional, a healthcare professional, or an automated applicator). In this sense, such data tends to be the most valuable information for the user who will receive the treatment plan, and this data can be accepted or rejected by the user.

[0278] Furthermore, it is important to note that any information contained in the treatment plan should be understood as treatment data.

[0279] For example, if the treatment plan generated directly by the computer platform includes cost information informing the user that the treatment will cost 10,000 monetary units, the user may accept or reject this cost. Likewise, if the treatment plan generated directly by the computer platform includes information on the number of sessions indicating that the treatment will be carried out in seven sessions, the user may accept or reject this information.

[0280] Therefore, if the cost data and number of sessions are accepted by the user, the treatment plan will be properly generated, based on the application seals S1, S2, S3, S4...SN. It is therefore understood that, if there is no objection from the user regarding the treatment data, the previously generated treatment plan will be implemented.

[0281] Alternatively, if at least one of the number of sessions and cost data is rejected by the user, the step of generating an updated treatment plan based on the user's requests is proposed. Thus, if the user objects to at least one of the treatment data, the step of receiving updated data from the user and generating an updated treatment plan is proposed, as described below.

[0282] For example, if the treatment plan directly generated by the computer platform has indicated a treatment item, for example, a number of sessions equal to 5 sessions and the user has, through the computer platform, rejected said item, it is then proposed to carry out the step of requesting the user for an update (update data) regarding the rejected item.

[0283] In this case, from the requested update, the user must inform whether he / she wishes to carry out the treatment plan in a greater or lesser number of sessions in relation to the number informed, alternatively, the user can, through the computer platform, indicate in how many sessions the user would like to carry out the treatment plan.

[0284] Once the user's update data has been received, the treatment plan update step is proposed, so that the treatment plan will now include the number of sessions data as informed by the user.

[0285] It is important to note that, if for some reason the update data provided by the user is not acceptable, the computing platform may issue an alert message, indicating that the number of sessions provided by the user is not permitted, based on the information contained in the application seals S1, S2, S3, S4...SN.

[0286] For example, if the user informs the desire to carry out the treatment in just one session, the alert message may be issued, thus indicating to the user the minimum number of sessions to carry out that specific treatment.

[0287] It is therefore understood that the present invention comprises the step of, after receiving the update data from the user, carrying out the step of verifying the viability of the received update data, to then generate an updated treatment plan (if the update data is considered viable).

[0288] Similar to the description above, the cost data can be accepted or rejected by the user.

[0289] For example, if the processing data, for example, the cost data directly generated by the computational platform and referring to the cost of 10,000 monetary units is rejected by the The computational platform will prompt the user to provide updated information. The user can then indicate that the reported cost is high, and the computational platform can then generate an updated treatment plan with a reduced cost, for example, the cost reported by the user.

[0290] As previously described, the stage of verifying the viability of the update data received is also proposed, for example, if the update data (new cost) informed by the user is not viable, the computer platform will issue an alert message, thus indicating to the user the impossibility of carrying out the treatment with the informed cost or also informing the minimum possible cost for carrying out that treatment.

[0291] By way of example only, the costs of a treatment can be reduced by replacing the type of product considered in the treatment and / or by replacing the applicator (whether a doctor or robot) who will perform the treatment and / or by changing the number of sessions.

[0292] In fully valid modalities, upon receiving the cost data linked to the treatment plan, the user may indicate, through the update data, the possibility of bearing a higher cost than that reported for carrying out the treatment.

[0293] For example, the cost data of 10,000 monetary units was generated considering the use of product A, which can be considered a mid-range product on the market. Thus, upon receiving the treatment plan with that product, the user can indicate the possibility of paying the cost of 15,000 monetary units and then undergoing treatment with product B, which is considered a premium product on the market.

[0294] Similarly, cost data can be updated from changing the professional responsible for implementing the treatment plan. For example, the cost data for 10,000 units was generated for professional A, who is considered to have average experience. Therefore, if the user wishes, they can request that the treatment plan be updated so that it is generated / implemented by professional B, who is considered to have extensive experience. Therefore, since the treatment plan will be implemented by a more experienced professional, the cost will, in theory, tend to be higher.

[0295] In an equally valid embodiment of the present invention, and before the treatment plan is generated, the step of motivating the user to inform, by way of example, a cost figure and a figure regarding the number of desirable sessions is proposed.

[0296] Thus, the user can freely specify, for example, how many sessions they wish to complete the treatment. The computer platform will then assess the feasibility of the number of sessions entered. If the number of sessions entered is feasible, the treatment plan will be generated. If not (the number of sessions is unfeasible), an alert message will be sent to the user, prompting them to submit the updated information, such as the previously provided description.

[0297] Additionally, or alternatively, before generating the treatment plan, the computer platform may prompt the user to provide a cost figure that the user is willing to pay for the treatment in question. Upon receiving the cost figure, the computer platform will automatically generate a treatment plan that matches the cost figure, including a specific number of sessions and type of product to be applied.

[0298] When the treatment plan is generated, it is proposed that this understand total cost information, that is, for the entire treatment, and also understand cost information for each session.

[0299] Thus, if the generated treatment plan indicates four sessions, it is proposed that the cost of each of the four sessions be reported separately, so that the user is aware of the separate costs and can, for example, issue update data for each of the sessions or for the entire treatment. It is therefore understood that, in accordance with the teachings of the present invention, the update data to be sent by the user may refer to the entire treatment, or they may refer to each of the treatment sessions.

[0300] It is also advantageous for the treatment plan to include an estimated date for each session, allowing the user to compare the treatment plan's completion date with the cost of each session and assess whether the user will be able to afford the respective cost on that date. If the user wishes to propose any changes to the treatment plan, an update can be submitted by the user.

[0301] Thus, with the present invention, the user has the freedom to, through user interaction with the computational platform, send update data for any information present in the treatment plan, so that the treatment plan to be generated can fit the user's needs and desires. Thus, and for example, the user can, therefore, accommodate the investment value that he or she is comfortable with.

[0302] Obviously, and as previously described, any update provided by the user must be validated by the computing platform, thus assessing the feasibility of carrying it out. of the treatment plan from the update provided by the user.

[0303] Thus, and as described previously, after presenting the objective diagnostic result (application seals), the system will ask the user how many sessions they wish to achieve the proposed goal, which will impact the amount of material to be used and the financial investment. The user can also present their budget for each stage of the treatment (or for the entire treatment), and the system will provide the number of sessions and quantity of products that fit the user's budget. The system can also indicate if the budget is not sufficient to achieve the user's requests or the desired result.

[0304] Therefore, the system is enabled to generate the treatment plan actively or responsively, such as indicating a treatment plan directly to the user (active) or calculating the treatment possibilities based, for example, on the budget sent by the user (responsive).

[0305] Thus, the treatment plan generated can be segmented by session, in which each session will include the respective treatment codes, the products to be used, as well as the aforementioned application doses.

[0306] Thus, and in reference to FIG. 44, there is an example of a treatment plan for a first session and which comprises four application actions AP1 to AP4, in which there is a first application AP1 in the treatment code Ck1, with a product designated as product A, with application of 3 aliquots of 0.1 ml on the right side and 3 aliquots of 0.1 ml on the left side.

[0307] Similarly, there is a second application AP2 in treatment code T1, with product A, with an application of 0.7 ml on the right side and 0.7 ml on the left side. Furthermore, and in reference to FIG. 44, there is a third application AP3 in treatment code Ck4 (0.5 ml on each side) and a fourth application in treatment code Ck3 (0.5 ml on each side).

[0308] It is noteworthy that the methodology and system proposed in the present invention can also, based on the treatment plan generated, indicate data relating to the number of syringes required to carry out the treatment plan, so that said data can be segmented, for example, by session, or even be indicated for the entire treatment.

[0309] Subsequently, the proposed step is to correlate the treatment plan with the application seals. More specifically, the proposed step is to generate and display the application seals linked to the treatment plan, thus enabling correct product application, promoting reproducibility, and reducing adverse events due to the lack of specific guidance on best practices in the healthcare field. In one embodiment, the step of correlating the treatment plan with the application seals could be performed for each treatment session, or even for each application action within that session, or even for the entire treatment.

[0310] Thus, with the application stamps, one has information on how to inject (apply) the substance (product) so that the treatment plan can be properly implemented. Thus, and referring to FIG. 45, there is the step of obtaining the application stamps linked to the treatment plan. More specifically, there is the step of obtaining the application stamps for the first session of the treatment plan, that is, the application stamps S1, S2, S3, and S4, which correspond to each of the four application actions AP1, AP2, AP3, and AP4.

[0311] Still referring to FIG. 45, it can be seen that the first treatment session comprises four applications, thus, and as illustrated in FIG. 45, four seals are generated and obtained. treatment, where each treatment seal refers to the application in a specific treatment code.

[0312] Thus, there is the first treatment seal S1 for the code Ck1, a second treatment seal S2 for the code T1, a third treatment seal S3 for the code Ck3, and a fourth treatment seal S4 for the code Ck4.

[0313] The application seals (such as seals S1 to S4) thus provide an indication of how the application should be performed, for example, and taking as a reference the application seal S1 of FIG. 45, there is an indication that the medical professional (or the automated applicator) should go to the code Ck1, so that, as said code is outlined by a blue circle, the professional (or automated applicator) will be aware that said code is a security code, subsequently, product A must be applied to the bone plane, so that to reach the bone plane a needle must be used and, at the time of application of the product, it must be distributed in aliquots, in which each aliquot must comprise an application of 0.1 ml.

[0314] Subsequently, once the application for application seal S1 has been completed, the applicator can move on to the next seal, that is, application seal S2, thus carrying out the application in treatment code T1 (second application action AP2).

[0315] In one embodiment of the present invention, it is proposed that the treatment code data provided on an application stamp be surrounded by a warning flag SA, as illustrated in FIGS. 43 (a) and 45. The warning flag SA can be understood as a circle of a certain color, such as blue or red, and which provides an indication to the applicator regarding the treatment code to be considered.

[0316] Thus, a blue SA attention flag indicates that That treatment code is a safety treatment code, while a red SA caution flag indicates that the treatment code is a caution code. Red halo (circle) codes denote proximity to important structures such as arteries that require greater caution, such as prior aspiration before injecting the product, as well as specific training in areas considered advanced.

[0317] This generates application stamps for each session of the treatment plan. FIGS. 46 to 48 illustrate the treatment plans and application stamps for the second, third, and fourth sessions, respectively, each of which comprises multiple application actions. It is therefore understood that each application action will have a corresponding application stamp.

[0318] In specific reference to Fig. 48(a), it is observed that for treatment codes Ck4 and Ck5, an application on the right side of the user's face was not suggested, precisely so that any asymmetry previously detected for the user during the facial scan can be corrected. It is noteworthy that any information (received data, scan) previously detected for a given user can be considered in the generated treatment plan.

[0319] Once the application stamps have been generated for each session, a CA application chain can then be generated for the generated treatment plan. The CA application chain can be understood as a group of application stamps linked to a specific user, where the application chain also includes the CT treatment identification code and the date on which the treatment plan was generated.

[0320] Thus, and with reference to FIG. 49, the application chain CA treatment can be segmented by sessions (portions), where the first session will comprise the set of application stamps used in the first session of the treatment plan, that is, stamps S1 to S4.

[0321] Thus, each portion of the CA application chain will comprise the set of application stamps used in the treatment plan session, in this way, the CA application chain acts as a consolidated block referring to the treatment plan of that respective user, in this way, the application chain (as well as the application stamps) can be sent to an applicator, such as a professional, medical professional, an automated applicator or a professional in the aesthetic health area.

[0322] Furthermore, once the processing has been completed, the CA application chain can be stored on the computing platform, or it can also be stored in a digital wallet linked to the user. Thus, the CA application chain allows tracking of the application history of that particular user, allowing the user to interact (e.g., click, tap, process) with a specific application seal stored in an application chain (or in a specific portion of the application chain) and access the information contained in that application seal—that is, the user will have access to all information related to the processing performed. The advantages of generating the application chain are enhanced as a given user may have performed dozens of treatments throughout their lifetime.

[0323] Thus, having generated the application seals S1, S2...SN as well as the application chain CA, these can be sent to an automated applicator and / or to a professional applicator. Thus, it is understood that the present invention comprises at least one of the following steps: sending at least one of the application seal and the application chain to an automated applicator used, and send at least one of the application seal and the application chain to a professional applicator.

[0324] In other words, it is understood that the application seals as well as the application chain can be sent to a medical professional and / or a beauty professional and / or an automated applicator (robot), so that the treatment plan can be put into practice.

[0325] Consequently, a medical professional (healthcare professional and / or aesthetics professional) who receives a specific application chain will be able to interpret it, thus reading each of the session application seals and thus applying the treatment plan to the user.

[0326] Similarly, an automated applicator that receives a given application chain can process it, interpreting the information contained therein and transmitting it to an automated mechanical arm responsible for applying the treatment plan.

[0327] As an additional feature of the teachings of the present invention, it is proposed that the computational platform 30 itself is capable of suggesting to the user a plurality of applicators (whether professional or automated) that would be capable of carrying out the treatment plan provided to the user.

[0328] Thus, based on a specific criterion (pre-determined criterion), such as the user's location (or native language), the computer platform 30 itself may suggest a list of applicators suitable for carrying out the treatment plan and located near the user. It is also proposed that the user be free to stipulate the maximum desired distance between the suggested applicators.

[0329] Additionally, or alternatively, the computing platform The computational platform is also capable of suggesting to the user only qualified (certified) applicators for a given procedure. For example, the computational platform 30 can be configured to indicate to the user clinics that have certified professionals, for example, in the already known MD Codes. Thus, this functionality of the computational platform acts as a "store locator" for the user, facilitating the indication of an applicator capable of carrying out the generated treatment plan.

[0330] Additionally, or alternatively, the teachings of the present invention are also capable of suggesting to the user a plurality of applicators, so that said suggestion is made based on the difficulty index linked to the treatment plan generated.

[0331] Furthermore, it is understood that the suggestion provided to the user includes at least one of: a suggestion of professional applicators, a suggestion of automated applicators and a suggestion of clinics that would be able to carry out the generated treatment plan.

[0332] In one modality, and regardless of the application mode (human or automated applicator), the application of the application chain (i.e., the performance of the treatment) can be recorded, for example, by a camera.

[0333] Thus, once the treatment has been performed, it is proposed that the CA application chain be updated with at least one DG recording data (video data), which DG recording data comprises the recording of the generated treatment plan. In one embodiment, the CA application chain could comprise a plurality of DG recording data, in which each DG recording data corresponds to a given application stamp. Additionally, it is fully acceptable to propose that the DG recording data be grouped, for example, for each session of the treatment plan or even for each session. of the application action AP1, AP2...APN of a given session. Thus, and with reference to FIG. 44, each of the four application actions of session 1 could comprise a DG recording data. Furthermore, it should be noted that obtaining, storing and sharing the recording data can be carried out with prior user authorization.

[0334] It should be noted that, by application action, we should understand each application existing in a treatment plan, as well as each application existing in a given session of the treatment plan. Thus, and with reference to FIG. 44, the indicated session comprises four application actions, these referenced as: first application action AP1, second application action AP2, third application action AP3 and fourth application action AP4.

[0335] Similarly, and now referring to Fig. 46(a), there is a fifth AP5, sixth AP6, seventh AP7 and eighth AP8 application actions.

[0336] Thus, by grouping the DG recording data for each application action of a given session, one can, for example, group the DG recording data according to a specific product that was considered in a treatment plan. For example, the manufacturer of product B considered in the treatment plan shown in Fig. 48(a) will be able to visualize, through the recording data segmented by application action, whether their product was properly applied to the user.

[0337] Furthermore, the CA application chain must also be updated with a code for the professional responsible for carrying out the processing, whether human or machine.

[0338] Thus, the CA application chain allows the computational platform manager to produce a variety of reports, segmented, for example, by the code of the professional who carried out the report. a specific treatment, by the code of the user who received the treatment, by the type of product applied, by the treatment code considered, among others.

[0339] It is worth noting that any information present in an application seal and / or present in a CA application chain and / or present in the computational platform and / or present in a treatment plan could be a parameter for generating a given report.

[0340] Furthermore, it is proposed that the generation of the CA application chain be accompanied by a CT cost data, thus, the present invention also comprises the step of generating a CT cost data from at least the application chain.

[0341] As previously described, the CT cost data can be understood as the cost related to the treatment plan implemented. Thus, upon receiving the treatment plan, the user will also receive a cost for the treatment in question, considering the chosen applicator. As previously described, the CT cost data can be reported for the entire treatment, or it can be segmented by session, application seal, or application action.

[0342] As an additional feature of the present invention, it is further proposed that each CA application chain further comprise at least one satisfaction index regarding the treatment performed. For example, said satisfaction index is understood as input from the user, thus indicating their satisfaction with the treatment performed as well as their satisfaction throughout the interactive process with the computational platform.

[0343] Furthermore, the teachings of the present invention are also beneficial since the computational platform can be used as a training platform for new applicators. For For example, using DG recording data, a computational platform manager (such as a cosmetic substance manufacturing company or a beauty clinic) can see whether a given applicator (whether human or robot) carried out the treatment plan as suggested in the application seals and in the application chain.

[0344] Thus, for example, a computer platform manager (or any user / entity responsible for providing training) can monitor DG recording data and provide, in real time, at least one compliance parameter, thus indicating whether or not the application performed is in compliance.

[0345] In one embodiment, said compliance parameter may be linked to each of the application seals S1, S2, S3, S4...SN that make up a given CA application chain. Thus, for each application seal, there will be an associated compliance parameter, that is, a parameter that indicates whether the substance was applied properly according to the application seal instructions. It is understood that the compliance parameter may be displayed on a screen of the computational platform and / or on a screen of an augmented reality device 1200.

[0346] Thus, the teachings of the present invention can be inserted into a computational platform that aims to train new professionals in the health area, thus acting as an academy, or aesthetic university, in which, from the user's interaction with a given professional, such as the user's interaction with a given graphical representation 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 and 1100 generated by artificial intelligence (as illustrated in FIGS. 56 and 57), a given treatment plan can be generated and consequently the user can receive appropriate training. In addition, there will be support from pro- Multidisciplinary professionals represented by "avatars" to clarify, educate, and plan in various areas relevant to a clinic's activities, including, but not limited to, healthcare, administrative, management, marketing (digital media and influencers, among others), legal, commercial, and accounting, as illustrated in FIG. 57. These avatars are designated with names containing the letters AI or AI, referring to artificial intelligence. For example, such an academy or aesthetics university could be commercially referred to as AKADEMIAE. In a valid embodiment, these avatars can be configured to provide the platform user (such as a user undergoing substance application training) with the compliance parameters linked to each of the application seals.

[0347] It is further understood that compliance parameters can be configured as at least text data, numeric data, audio data, video data, data represented in an augmented reality environment, as well as a combination of these.

[0348] For example, the compliance parameter can be configured as text, indicating to the user that the seal was applied correctly. More specifically, this parameter can be represented as the following message: "incorrect application" or "correct application."

[0349] More specifically, it is proposed that a corresponding compliance parameter be generated for each piece of data included in a given application seal. Thus, it is proposed that a compliance parameter be generated that is linked to the treatment code, application product, application layer, application device, application method, and active number (dose). This makes it possible to specifically determine the point of compliance (or noncompliance) during the application of the substance. For example, if there is a noncompliance related to the application product, it becomes possible to identify that the substance was applied with a product not specified in the application label. Therefore, the present invention proposes the step of generating a compliance parameter for each application label and / or generating a compliance parameter for each of the data items included in the application label.

[0350] In a valid embodiment, a user's interaction with the computing platform (such as a user receiving training) could be conducted in the form of a survey, which would be displayed on the computing platform's screen. Equally validly, this interaction could be conducted by a graphical representation generated by artificial intelligence, as previously described.

[0351] The survey presents the user in training with a series of questions related to the application of a specific substance, and the user is tasked with answering them through interaction with the computer platform. In one embodiment, once the user has submitted the answer, the graphical representation generated by artificial intelligence can indicate, through audio (voice), whether the answer is correct or not, thus generating a compliance parameter.

[0352] It is also proposed that the survey be correlated with the application seals. In this sense, and as illustrated in Figure 73, interaction with the user could occur through the display of a specific application seal SN on the computer platform screen, as well as through asking the user to indicate "how the application seal for the treatment code Jw1 can be injected”. In one modality, this question could be asked by voice, through the graphical representation generated by artificial intelligence.

[0353] Furthermore, the display of the application seal on the computer platform 30 screen could initially omit some data from the application seal, such as data relating to the application layer and the application device, as illustrated in Figure 73 (since this data is related to the question asked). Subsequently, after the user submits their answer, the application seal could be displayed to the user in its entirety.

[0354] In an equally valid modality, the already mentioned graphical representations generated by artificial intelligence could be used not only in the interaction with a user who wishes to receive a treatment plan, but also in the interaction with a user of the computer platform who is receiving a certain training.

[0355] In this way, the graphical representation generated by artificial intelligence 1200 can, for example, present to the user in training a certain “case study” 3000 as well as present to the user an explanation (whether by voice, text, video and / or a combination thereof) regarding the selection of products to be considered for the case study in question, as illustrated by way of example in figure 74.

[0356] Additionally, the graphical representation generated by artificial intelligence 1200 can also associate a given application seal SN with the case study 3000 in question, thus providing an explanation to the user (whether by voice, text, video and / or a combination thereof) regarding how a given product should be applied in that case study, as illustrated in figure 75.

[0357] The teachings proposed in the present invention are still- able to display a set of instructions on the computer platform screen, said set of instructions thus providing instructions on how a given substance should be applied. Said set of instructions can be understood as graphical, video, audio, text instructions (or a combination of these), and can be viewed by the platform user, such as the user receiving training.

[0358] Thus, referring to Figure 76, there is an application instruction 5000 that tells the user how to read and interpret a given application seal. Application instruction 5000 is understood to be a graphical instruction, generated by the computing platform and displayed over a graphical representation (photo, video, and / or artificial intelligence-generated representation) of the case study 3000 in question. It is thus understood that application instruction 5000 is displayed over the graphical representation of case study 3000.

[0359] It is proposed that the graphical instruction 5000 be provided in conjunction with an audible instruction (such as the voice of the avatar 1200), said audible instruction thus indicating to the user how to apply the substance in question. For example, in the case of the illustration in Figure 76, said audible instruction could indicate to the user in training: "Place the patient with the chin up and mark Jw4 and Jw5 below the edge of the jaw, be aware that Jw4 is three times the length of Jw5." Additionally, both the graphical instruction 5000 and the audible instruction could indicate to the user in training how a particular application label SN should be read and interpreted.

[0360] In an equally valid embodiment, and as illustrated in Figure 77, the application instruction 1700' could be configured in the form of a graphical representation (such as a circle) superimposed on the face of the case study 3000 and which indicates to the user in training the positioning point of the cannula. Additional application instructions 6000 could be arranged, these graphically indicating, on the representation of the case study 3000, the application points and their respective volumes.

[0361] Additionally, and with reference to Figure 78, the user in training may be encouraged, through the computer platform, to indicate the treatment codes that the user deems appropriate for a given case study 3000. Thus, interacting with the computer platform, the user may suggest the treatment codes (for example, by clicking on the appropriate codes), and these will be inserted into a test stamp 4000 that may later be sent to the computer platform's database. In one embodiment, the test stamp could also be sent to an automated applicator.

[0362] Subsequently, it is proposed that a comparison be made between the test seal 4000 submitted by the user and a template seal (not shown) previously stored in the computational platform. Furthermore, the computational platform is capable of generating a compliance score, thus indicating to the user their accuracy in the chosen treatment codes. The template seal is understood as previously stored data that includes the correct treatment codes for the case study 3000 in question.

[0363] It is therefore understood that the teachings of the present invention can be applied in an educational platform, both for health professionals and other related professionals, as well as for patients.

[0364] Furthermore, the medical professional himself can evaluate the recording data, thus viewing the video of the application carried out by himself and thus determining possible points of improvement. Ihoria.

[0365] Generating and storing DG recording data is equally beneficial to the user who received the treatment plan, as it provides confirmation that the treatment plan was properly followed as suggested. Thus, from the CA application chain, it becomes possible to track the history of applications performed, for example, for a specific user.

[0366] Thus, and in accordance with the previously described description, it is understood that one of the advantages of the application chain lies in the possibility of tracking the data linked to the treatment plan, thus acting, for example, as legal support (for example, for regulatory bodies) regarding the treatment plans generated.

[0367] Thus, the teachings of the present invention are beneficial not only to the user receiving the treatment plan, but also, for example, to a company manufacturing aesthetic substances, which uses the methodology, system, and computational platform proposed in the present invention and which can be used, for example, to generate thousands of treatment plans simultaneously. It is therefore understood that the present invention comprises the step of generating a plurality of treatment plans simultaneously.

[0368] In one embodiment, the teachings of the present invention could be applied, for example, in a medical office (temporary clinic) and / or at a specialized trade show in the aesthetic and / or medical sector, which trade show could include a totem and / or a stand equipped with a computer platform that uses the methodology described herein. The application of the teachings of the present invention in an aesthetic clinic would also be fully acceptable.

[0369] Once the treatment is completed, the computer platform can display a representation of the user's face as it appeared before and after the treatment, allowing the user (and / or medical professional) to evaluate the effectiveness of the treatment. This display may occur with the user's prior authorization.

[0370] In one embodiment, the evaluation of the effectiveness of the treatment can also be obtained from the arrangement of reference lines LR on the user's face, which reference lines LR act as a reference to evaluate whether a given portion of the user is aesthetically and scientifically suitable. For example, the reference lines can be useful to evaluate whether a portion of the user is sagging (drooping) or not. Such reference lines LR are illustrated by way of example in FIG. 50.

[0371] Additionally, or alternatively, the evaluation of the efficiency of the treatment can still be obtained from the segmentation of the portion of the user in the plurality of quadrants, and thus assigning indexes to each of the quadrants of the plurality of quadrants, as previously described.

[0372] In a valid embodiment of the present invention, the application seals as well as the application chain could be read and processed by an augmented reality device. It is therefore understood that the present invention proposes the step of associating the treatment plan with an augmented reality environment. In valid embodiments, the step of associating the treatment plan with an augmented reality environment can be understood as the step of applying the treatment plan in an augmented reality environment.

[0373] An augmented reality environment is understood as an environment that mixes the real context with the virtual context, thus, through the use of an electronic device (such as a augmented reality glasses), the user is able to perceive virtual objects arranged in a real context.

[0374] In this way, one can, for example, use the augmented reality device as an assistance and / or training tool regarding the application of the training plan.

[0375] Thus, and with reference to FIG. 62, a user of the present methodology, through the use of an augmented reality device 1200, could receive and view a set of instructions 1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020, 2100, 5000, 6000 and 1700' linked to the application of the substance to the patient, so that said set of instructions 1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020, 2100, 5000, 6000 and 1700' are received and viewed in real time by the user, in the as the user visualizes (looks) at the patient who will receive the application.

[0376] Thus, and also referring to FIG. 63, using the augmented reality device 1200, the user, when viewing the patient who will receive the application, may receive and view a set of instructions that assist the professional during the application. Said set of instructions may be understood as graphical, video, audio, text instructions (or a combination thereof), and which can be viewed by the professional using the augmented reality device 1200.

[0377] Thus, a first instruction 1300 can be generated that indicates the location on the patient's face where the user should make a certain marking.

[0378] It is understood that said first instruction 1300 is configured as a computer-generated instruction (more specifically, by the augmented reality device 1200) and that it can be viewed by the user through the use of the augmented reality device. augmented 1200. It is thus understood that the first instruction 1300 is an instruction generated and visible in an augmented reality environment.

[0379] More specifically, it is proposed that the first instruction 1300 be viewed by the user superimposed on a representation of the patient, such as a representation of a photo of the patient and / or a real representation of the patient. By real representation of the patient, it is understood that, when using the augmented reality device 1200 and looking at the patient's face, the user will view the first instruction 1300 superimposed on the patient's face, thus allowing the user to make the necessary markings 1400 on the patient's face, as illustrated in FIG. 64.

[0380] It is therefore understood that the first instruction 1300 is a virtual instruction, while the marking 1400 must be understood as a real marking, that is, effectively carried out on the patient.

[0381] Furthermore, and as can be seen from FIG. 63, the first instruction 1300 can be understood as a graphical instruction, configured as the arrangement of lines that indicate the marking location on the patient's face.

[0382] In conjunction with the display of the first instruction 1300, an additional instruction 1310 could be arranged in the augmented reality environment and thus be perceptible to the user, said additional instruction 1310 (first additional instruction 1310) configured as a text instruction and indicating to the user the need for marking on the patient's face.

[0383] It is thus understood that the augmented reality environment allows the visualization of combined instructions, whether these instructions are graphic, text, video, audio, sensory, among others. Validly, the augmented reality environment also allows the visualization of compliance parameters, as already described above. subsequently. Thus, the user using the augmented reality device 1200 can be understood as a user in training, such that the compliance parameters are sent to the device 1200 from an entity providing said training. It is thus understood that the augmented reality device allows the sending, receiving, and processing of data. In harmony with the description of the present invention, it is further understood that the computing platform is also capable of sending, receiving, and processing data.

[0384] Referring now to FIG. 65, a second instruction 1500 may be displayed to the user and viewed through the augmented reality device 1200, said second instruction 1500 configured to indicate to the user the location of the upper and lower markings of the zygomatic margins. It is understood that the second instruction 1500 acts as a reference, created in real time and superimposed in relation to the patient's face, and that facilitates the making of the markings by the patient, said marking 1600 being effectively illustrated in FIG. 66.

[0385] Additional instructions can be generated and viewed by the user using the augmented reality device, such as instructions indicating the need to clean a portion of the user's face as well as the need for a certain portion of the user's face to be pinched.

[0386] With reference to FIG. 67, an additional instruction, herein referred to as third instruction 1700, can be viewed by the user and which indicates, through a red circle superimposed on the patient's face, the exact location where the introducer should be placed, so that a fourth instruction 1800 can still be virtually generated to graphically indicate the need to perform circular movements to enlarge the hole, as illustrated in FIG. 68. Obviously, reference to a red circle should not be considered as a limiting feature of the present invention.

[0387] It is understood that additional instructions 1710 and 1810 (referred to as second and third additional instructions) can be respectively combined with the third instruction 1700 and fourth instruction 1800, said additional instructions 1710 and 1810 indicating, in text form, an action that must be performed by the user of the methodology.

[0388] Referring now to FIG. 69, a fifth instruction 1900 could be generated that indicates the step of positioning the application element, such as the cannula.

[0389] Subsequently, a sixth instruction 2000 could be generated, as illustrated in FIG. 70, thus indicating the need to administer the substance. In this case, it is proposed that said sixth instruction 2000 be understood as a virtual illustration of one of the application labels that is part of that patient's treatment plan. Thus, the user using the augmented reality device 1200 will virtually view the application label containing all the instructions regarding the application.

[0390] During administration, additional instructions 2010 and 2020 may be generated to assist the user in administering the substance. Such instructions may refer, for example, to a direction for administering the substance (instruction 2010) as well as to a virtual meter 2020 for the amount of substance already injected. The additional instructions 2010 and 2020 may be understood as a fourth additional instruction and a fifth additional instruction, respectively.

[0391] Additionally, an audio instruction may be played to the professional using the augmented reality device, for example, and with reference to FIG. 70, said audio instruction may comment on the information contained in the application seal, as the audio instruction could reproduce the following words: “Inject into Ck1 with hyaluronic acid (VM), in the sub-SMAS layer, in a linear retrograde technique with a total of 0.5 ml”.

[0392] It should be noted that any instruction generated and displayed through the augmented reality device 1200 could be configured as an audio instruction. Furthermore, it should be noted that a given instruction could be generated either graphically (such as text, video, or through arrows, circles, etc.) or audibly. Thus, the professional could see the instruction as well as hear it.

[0393] Once the application is complete, additional instructions can be generated for the user to view, such as instructions for removing the cannula, stopping any bleeding, confirming the volume of substance actually applied, and cleaning the application area.

[0394] It should be noted that any of the instructions commented above can be understood as an instruction that is part of the set of instructions generated by the augmented reality device 1200, that is, any of the commented instructions must be understood as a virtual instruction, that is, an instruction perceptible in an augmented reality environment.

[0395] Additionally, any of the instructions mentioned above can be understood as an instruction that is part of the instruction set, an instruction that can be displayed directly on the computer platform screen.

[0396] An additional feature of the present invention and linked to the use of the augmented reality device 1200 is the possibility of using an anatomy tool.

[0397] In short, the anatomy tool makes it possible, at any time, such as before performing a procedure, the professional (user of the methodology) reviews the patient's anatomy related to the application in question.

[0398] Thus, through the use of the augmented reality device 1200, a graphic indication 2100 (also referred to as the seventh instruction) can be placed on the patient's face and consequently be viewed by the user of the methodology, so that said graphic indication 2100 can represent the patient's arteries.

[0399] FIG. 72 is an illustration of the graphic indication 2100 displayed on the patient's face. It shows the external carotid artery and the facial artery with the submental branch. The inferior and superior labial arteries can also be seen, followed by the lateral and angular nasal arteries.

[0400] It is proposed that, during the application of the substance, the professional be able to review, at any time, the relevant anatomical structure of the patient considering the treatment plan generated.

[0401] In one embodiment, the representation of the graphic indication 2100 referring to the anatomical structure of the patient could be viewed by the professional through the augmented reality device by displaying a video, in this way, said video could, sequentially, display the arteries mentioned above.

[0402] In one embodiment, the graphic indication 2100 could be configured as a solid line, arranged in red, and representing the patient's arteries, so that said graphic indication would be superimposed on the patient's face, thus facilitating the visualization of the graphic indication 2100 by the medical professional. In one embodiment, said graphic indication could be virtually arranged over the patient's actual face and, through the use of the augmented reality device, that is, when looking at the patient, the user will virtually visualize the graphic indication 2100. In embodiments equally valid, the graphic indication 2100 could be placed over a photo and / or video of the patient.

[0403] Furthermore, it is understood that the graphic indication 2100 is a virtual graphic indication, that is, viewed in an augmented reality environment and through the use of the augmented reality device.

[0404] In accordance with the previously described description, the present invention also describes a computer system for consultation, diagnostic evaluation, and financial planning related to a treatment plan. It is understood that said system is capable of performing all steps of the described method using a computer platform.

[0405] Thus, the user can interact with the computational platform and thus perform the steps of the method described.

[0406] It is thus understood that the computing platform comprises an input block 31 configured to receive user information, a memory, a processor, as well as a comparator module to perform the comparisons described and thus assess whether there is a need for aesthetic treatment.

[0407] Thus, according to the teachings described, it is understood that the invention can be implemented in a mobile application of an electronic device, such as a cell phone.

[0408] Furthermore, it is understood that the teachings of the present invention can be applied using an augmented reality device.

[0409] Furthermore, and as described, the invention is also based on the use of servers that communicate with the computing platform, such as servers located in the cloud.

[0410] It is thus understood that the invention also addresses a non-transitory computer-readable medium comprising a set instructions capable of executing the steps of the previously described method as well as executing the functionalities of the described system.

[0411] Finally, and in accordance with the teachings of the present invention, the step of scanning, on the computational platform, at least a portion of the user results in obtaining an aesthetic signal, which signal can assume a treatment state or a non-treatment state.

[0412] As described, it is understood that an aesthetic marker that assumes a treatment state results in the obtaining of a treatment code. Furthermore, said aesthetic marker can be obtained in several ways, such as by segmenting the user's face into a plurality of quadrants and assigning an index (value) to each of the quadrants, or to a set of quadrants, as previously described.

[0413] Finally, the step of scanning, on the computational platform, at least a portion of the user can be performed based on the face hierarchies H1, H2, H3, H4 and H5 previously addressed in US patent 11,602,303. It should be noted that scanning the face based on the hierarchies should not be considered as a limiting characteristic of the present invention, so that performing a scan not tied to the hierarchies would be fully acceptable.

[0414] It is important to note that the teachings of the present invention can be absorbed by anyone, such as those who wish to receive a treatment plan that includes a specific treatment code. Thus, the teachings of the present invention are beneficial, for example, to users who wish to receive a treatment, such as an aesthetic treatment. In any case, it is important to note that the teachings of the present invention are not limited to aesthetic treatment plans.

[0415] Furthermore, the teachings of the present invention can be also absorbed by healthcare professionals, such as aesthetic health professionals. Obviously, medical professionals can also absorb the teachings of the present invention; however, it is emphasized that the teachings described here can be absorbed by anyone, but this does not necessarily have to be a physician.

[0416] Likewise, managers of health, beauty and medical companies can also absorb the teachings of this invention.

[0417] The professional administering the treatment must be qualified to administer the treatment in accordance with each country's regulatory standards. The system can understand information regarding each country's regulations.

[0418] Furthermore, it is understood that the present invention also addresses a system capable of carrying out the described methodology.

[0419] Furthermore, to obtain the final treatment plan (i.e., to generate the treatment plan), the methodology described will provide the user with options, including simulations of the aging process and simulations of possible outcomes through treatment, as shown in FIGS. 58 and 61 (these can be generated, for example, through artificial intelligence), thus identifying inconsistencies and consistencies between the subjective (impulsive) and graphic (objective) assessment performed by the user and the assessment performed from the face scan. Thus, the methodology described in the present invention proposes the step of asking the user whether they wish to continue with the subjective and graphic assessment or with the assessment performed from the face and / or body scan, depending on the area focused on by the patient.

[0420] Thus, the methodology described in the present invention also comprises the step of prioritizing, in the treatment plan, at least one of the final aesthetic data set, the final emotional data set, the final social data set, and the user's face scan.

[0421] It is worth noting that, if the user so wishes, the final set of aesthetic data, the final set of emotional data and the final set of social data can be disregarded when generating the treatment plan, thus prioritizing only the generation of the treatment plan based on scanning the user's face and / or body.

[0422] Furthermore, the teachings of the present invention allow for the performance of before and after simulations for a given portion of the user, such as their face and / or body, in addition to simulations of both the facial and body aging process.

[0423] It is also noteworthy that the teachings of the present invention can be absorbed into any portion of the user, whether into the user's face, the user's body, or any portion of the user.

[0424] Finally, it is understood that, according to the teachings of the present invention, the treatment plan can be generated from the application stamps, as well as the application stamps can be generated from the treatment plan.

[0425] From the description provided, it is understood that the teachings of the present invention can be used by users from any location, thus eliminating geographical and communication barriers, and accommodating different regulatory and legal rules on a single computing platform.

[0426] Furthermore, and as described, the teachings of the present invention can be used not only to personalize treatment plans, but also to personalize the training of professionals according to their level of experience, specialty and individual needs.

[0427] Additionally, through the already described compliance parameters, the present invention allows the provision of instant feedback related to the application of the substance, thus allowing the identification of areas for improvement and providing specific guidance to help injectors improve their skills.

[0428] Furthermore, certifications can also be conducted and granted within the platform described here for injectors who successfully complete courses or programs on the platform, adding value to their resume and helping to validate their skills.

[0429] In one embodiment, the teachings of the present invention may be utilized in the form of a computational platform that acts as a virtual laboratory, thus allowing users to practice their skills and procedural techniques in a simulated environment, using, for example, an artificial intelligence-generated avatar as patients (case study) as well as using any other form of test model (such as using photographs and videos of people). Thus, the teachings of the present invention provide a hands-on learning experience, further enabling the application of the tests in an augmented reality environment, thus allowing users to refine their skills and develop confidence in performing aesthetic procedures safely and effectively.

[0430] Consistent with the description provided, the teachings of the present invention incorporate financial planning tools to estimate treatment costs, outline payment options, and facilitate transparent communication about pricing and financial responsibilities. Users can explore different financing alternatives and budgeting strategies to make informed decisions. trained on their aesthetic treatments.

[0431] A significant advantage of the teachings proposed here is the ability to detect errors that may be made by injectors during injections. These errors are readily captured and transmitted (e.g., through DG recording data, as previously described), thus serving as a valuable database of injector practices. By highlighting areas for improvement, training, or further study, this feedback mechanism allows injectors to refine their skills and gain experience more effectively.

[0432] Furthermore, the teachings of the present invention can also be used as an immersive reality tool (virtual reality and / or augmented reality) that allows users to practice technical skills in a realistic virtual environment. These simulations can replicate treatment rooms, equipment, and patient interactions, providing a safe and controlled space for users to refine their techniques and build confidence. Whether learning new code or refining existing skills, the present invention supports this by providing visual overlays, anatomical landmarks, and user-tailored step-by-step instructions, such as previously described and referenced to the instruction set 1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020, 2100, 5000, 6000, and 1700' and compliance parameters.It is understood that the instruction set can be displayed directly on the computing platform and / or through the augmented reality device. The same applies to compliance parameters.

[0433] Based on the description provided, it is understood that the teachings of the present invention are beneficial at least for professionals in the health / aesthetics field, such as professionals who apply injectable substances, to the general public who wish to receive a treatment plan, to cosmetic companies and / or pharmaceutical companies, as well as to students, educational institutions and users who wish to receive some type of training (or provide training).

[0434] In accordance with the previously described description, the present invention also addresses a device 30 capable of performing the steps of the described method. In one embodiment, said device 30 may be understood as a cell phone, tablet, television, totem, or any other equivalent device.

[0435] As described, device 30 comprises at least a processor, a display, a camera, and memory. As already described, these components can be understood as the input block 31 of device 30. It is understood that device 30 is capable of performing any of the steps of the proposed method.

[0436] Thus, in summary, the device 30, through its input block 31, is capable of receiving a plurality of general input data from the user and generating a treatment identification code from the plurality of general input data. The device 30 is also capable of collecting a plurality of query data related to the user and, additionally, scanning (e.g., through the device's camera) at least a portion of the user. Thus, the device 30, through its processor, is capable of generating a treatment plan from a scan of the user's face.

[0437] As already mentioned, the device 30 proposed in the present invention is capable of performing any of the steps of the proposed method. Thus, it is understood that the device 30 is capable of segmenting a portion of the user (such as the user's face) into a plurality of quadrants and assigning at least one index to at least one of the quadrants of the plurality of quadrants.

[0438] Thus, it is understood that the device 30 is also capable of defining portions of the monitoring user, consideration portions and treatment portions, so that said portions are defined through the previously mentioned aesthetic variation index.

[0439] It is understood that the device 30 is further capable of obtaining at least one treatment code from scanning the user's face and displaying the treatment codes on a screen of the device.

[0440] Furthermore, the device 30 is also capable of generating, sending, receiving, processing and displaying at least one application seal S1, S2, S3, S4...SN linked to the user. The characteristics of the application seal S1, S2, S3, S4...SN have already been previously described.

[0441] As already described, in one embodiment, the application stamp S1, S2, S3, S4...SN may be illustrated on the screen of the device 30. Further, the application stamp S1, S2, S3, S4...SN may be sent from the device 30 to an automated applicator.

[0442] In accordance with the previously described description, the device 30 proposed in the present invention, through its processor, is also capable of generating a CA application chain from the grouping of a set of application stamps S1, S2, S3, S4...SN linked to the user. As already described, the CA application chain could also be sent, from the device 30, to an automated applicator.

[0443] It is further understood that the proposed device 30 is capable of storing data in the application stamps S1, S2, S3, S4...SN and / or in the application chain CA, such as storing at least one recording data DG in the application stamp and / or in the application chain.

[0444] The device 30 proposed in the present invention is capable of performing any step of the method already described. Thus, the device 30 described in the present invention is capable of generating a graphical representation of a professional, in which the graphical representation is generated by means of artificial intelligence, so that the device 30 is still able to conduct an interaction with the user, said interaction being conducted, for example, through graphical representation.

[0445] As already described, the device 30 proposed in the present invention is also capable of associating the treatment plan with an augmented reality environment.

[0446] It is therefore understood that the present invention also describes a device 30 capable of generating a treatment plan.

[0447] The present invention also describes an automated applicator capable of communicating with the device 30 proposed in the present invention. Thus, the automated applicator is capable of communicating, for example, with a cell phone 30 that performs the steps of the method proposed in the present invention.

[0448] This automated applicator can be understood as an applicator of aesthetic substances, such as injectable substances. Thus, in accordance with the description previously provided, the automated applicator is capable of receiving an application seal S1, S2, S3, S4...SN and thus reading (processing) said application seal S1, S2, S3, S4...SN.

[0449] In one embodiment, the sending of the application seal S1, S2, S3, S4...SN from the device 30 (cell phone, computer, or any other equivalent means) to the automated applicator could occur via an internet connection; however, any sending method that uses a communication protocol is acceptable. Reading the application seal S1, S2, S3, S4...SN by the automated applicator should be understood as the processing of the application seal S1, S2, S3, S4...SN (computational processing) by the automated applicator. It is therefore understood that the automated applicator comprises at least a processor and memory.

[0450] Thus, upon receiving the S1, S2, S3, S4...SN application seal, a mechanical arm of the automated applicator will move, thus changing from a resting (stationary) state to a moving state. It is understood that the mechanical arm of the automated applicator is associated with a substance injection device (such as a syringe).

[0451] In one embodiment, the automated applicator may be located in a geographic location different from the geographic location in which the device 30 is located.

[0452] In one embodiment, the automated applicator is capable of reading and processing each of the data included in an application stamp and applying the substance in accordance with the data set out in the application stamp.

[0453] It is also understood that the automated applicator is capable of reading and processing the information contained in a CA application chain.

[0454] It is therefore understood that the present invention also addresses an automated applicator associated with device 30, said device 30 capable of carrying out the steps of the proposed method.

[0455] Having described a preferred embodiment, it should be understood that the scope of the present invention encompasses other possible variations, being limited only by the content of the appended claims, including possible equivalents.

Claims

CLAIMS 1. Computational method for consultation, diagnostic evaluation and financial planning to generate a treatment plan related to a user, characterized by the fact that it comprises the steps of: receiving, in a computational platform, a plurality of general input data from a given user, generating a treatment identification code from the plurality of general input data, collecting a plurality of consultation data related to the user, scanning, in the computational platform, at least a portion of the user, and generating the treatment plan at least from the scanning of at least a portion of the user.

2. Method, according to claim 1, characterized by the fact that it further comprises the step of: obtaining at least a first set of aesthetic data of the user from an impulsive representation of the user, obtaining at least a second set of aesthetic data of the user from a graphical representation of the user, evaluating, in a comparator module, whether there is a consistency between each of the aesthetic data of the first set of aesthetic data and the second set of aesthetic data, if a consistency is not detected, outputting a representation perceivable to the user and encouraging the user, through the computational platform, to input a final set of aesthetic data, alternatively, if a consistency is detected, outputting a representation perceivable to the user and transforming the first set of data of the aesthetics and the second set of aesthetic data into the final set of aesthetic data.

3. Method, according to any one of the preceding claims, characterized by the fact that it further comprises the step of: obtaining a first set of emotional data of the user from the first set of aesthetic data, obtaining a second set of emotional data of the user from the second set of aesthetic data, evaluating, in the comparator module, whether there is a consistency between each of the emotional data of the first set of emotional data and each of the emotional data of the second set of emotional data, if a consistency is not detected, output a representation perceivable to the user, alternatively, if a consistency is detected, output a representation perceivable to the user and transforming the first set of emotional data and the second set of emotional data into a final set of emotional data.

4. Method according to any one of the preceding claims, characterized in that it further comprises the steps of: obtaining, from a socializing block, a plurality of favorable social data linked to the user and a plurality of unfavorable social data linked to the user, consolidating the plurality of favorable social data and the plurality of unfavorable social data into a final set of social data.

5. Method according to any one of the preceding claims, characterized in that it further comprises the steps of: generating a difficulty index from at least the evaluation of the final set of aesthetic data, the final set of emotional data, and the final set of social data, and displaying the difficulty index, through the computational platform, to the user, in which the method further comprises at least one of the steps of: suggesting to the user a plurality of applicators linked to the difficulty index obtained, in which the plurality of applicators is segmented between professional applicators and automated applicators, suggesting to the user a plurality of applicators based on a predetermined criterion, in which the predetermined criterion is at least one of: a location of the user, a native language of the user, and suggesting to the user a plurality of applicators who are qualified in a given procedure.

6. Method, according to any one of the preceding claims, characterized by the fact that the step of scanning, through the computational platform, at least a portion of the user, further comprises the step of scanning the portion of the user horizontally and vertically, and further considering a frontal portion, an oblique portion and a profile portion of the user, in which the scanning step further comprises the step of segmenting the portion of the user into a plurality of segments.

7. The method of any one of the preceding claims, further comprising the step of correlating the scan of the user portion with at least one of a plurality of virtual positive social data, in a plurality of virtual negative social data and a set of virtual emotional data linked to the user, in which the correlating step further comprises the step of scanning a portion of the user and generating an alert indication for each virtual emotional data considered.

8. Method, according to any one of the preceding claims, characterized by the fact that the step of scanning, on the computational platform, at least a portion of the user further comprises the step of: segmenting the portion of the user into a plurality of quadrants, assigning at least one index to at least one of the quadrants of the plurality of quadrants, and generating an aesthetic beacon from the segmentation of the portion of the user into the plurality of quadrants.

9. Method, according to any one of the preceding claims, characterized by the fact that the step of scanning, in the computing platform, at least a portion of the user further comprises the step of performing, through the computing platform, a dynamic scan of the user, in which the step of performing a dynamic scan of the user further comprises the step of: comparing portions of the user in a static state and in a dynamic state, mirroring at least a portion of the user, in which the step of mirroring at least a portion of the user further comprises at least the step of: comparing a first mirroring of the user with a second mirroring of the user and, identifying a final mirroring from the comparison between the first mirroring of the user with the second mirroring. in user's mind.

10. Method according to any one of the preceding claims, characterized in that the step of comparing portions of the user in a static state and in a dynamic state further comprises the step of: generating, for each comparison performed, the aesthetic flag, in which the aesthetic flag assumes at least one treatment state and one non-treatment state, in which the method further comprises the step of: obtaining and storing at least one treatment code if the aesthetic flag assumes a treatment state.

11. Method, according to any one of the preceding claims, characterized by the fact that the step of comparing portions of the user in a static state and in a dynamic state further comprises the step of: assigning a static index and a dynamic index to each portion of the user, the static index linked to the static state and the dynamic index linked to the dynamic state, comparing the static index and the dynamic index for each portion of the user, evaluating whether there is an aesthetically positive or aesthetically negative variation from the comparison between the static index and the dynamic index, if an aesthetically negative variation is detected, performing the step of assigning the aesthetic flag to the treatment state, and if an aesthetically positive variation is detected, performing the step of assigning the aesthetic flag to the non-treatment state.

12. The method of any one of claims preceding conditions, characterized by the fact that the step of scanning, on the computational platform, at least a portion of the user also comprises at least one of the following steps: comparing at least a portion of the user with at least a portion considered ideal, and generating, for each comparison made, the aesthetic flag, in which the aesthetic flag assumes at least the treatment state and the non-treatment state, in which the method also comprises the step of: obtaining and storing at least one treatment code if the aesthetic flag assumes the treatment state.

13. Method, according to any one of the preceding claims, characterized by the fact that the step of comparing at least one portion of the user with at least one portion considered ideal further comprises the step of: comparing, for each portion of the user, a real aesthetic data with an aesthetic data considered ideal, in which the aesthetic data considered ideal is a data previously stored in the computer platform, in which the aesthetic data considered ideal is obtained from at least one of the following forms: clinical tests, provided by the computer platform itself, proposed by an artificial intelligence tool associated with the computer platform, in which: the aesthetic data considered ideal is related to a certain ethnicity and age range related to the user, in which the method further comprises the step of: updating the aesthetic data considered ideal from ideal aesthetic learning data.

14. Method according to any one of the preceding claims, characterized in that the step of scanning, on the computing platform, at least a portion of the user com- further comprises at least one of the following steps: defining monitoring user portions, defining consideration user portions, defining treatment user portions, wherein the monitoring, consideration, and treatment user portions are obtained from an aesthetic variation index (Aest), wherein the aesthetic variation index (Aest) is obtained from the following expression: Aest = |lestideai - lestreai |, where: lestideai should be understood as an ideal aesthetic index, and lestreai should be understood as a real aesthetic index.

15. Method according to any one of the preceding claims, characterized in that it further comprises the step of obtaining at least one treatment code from the step of scanning at least a portion of the user, and displaying the treatment codes on a portion of the user, in which the method further comprises the step of: for each treatment code obtained, also obtaining a related dose, and displaying the related dose on the computational platform.

16. Method according to any one of the preceding claims, characterized in that it further comprises the step of: from the treatment codes, generating at least one application seal (S1, S2, S3, S4...SN) linked to the user, in which the application seal (S1, S2, S3, S4...SN) comprises at least: a treatment code data, an application product data, an application layer data, an application device data, an application mode data, an active number data, in which the application stamp is configured as at least one of: a computer-readable application stamp and a user-readable application stamp.

17. Method, according to any one of the preceding claims, characterized by the fact that it further comprises the steps of: generating the treatment plan from the application stamps (S1, S2, S3, S4...SN), in which the treatment plan comprises treatment data, in which the treatment data represents at least one of: data on the number of treatment sessions, data on the cost of the treatment, data indicating the person responsible for carrying out the treatment plan, in which the method further comprises the step of: evaluating whether there is a dispute from the user regarding at least one of the treatment data, in which, if there is a dispute, performing the step of receiving update data from the user and generating an updated treatment plan, and if there is no dispute, performing the step of implementing the generated treatment plan.

18. Method, according to any one of the preceding claims, characterized by the fact that it further comprises the steps of: receiving, on the computational platform, an input data relating to at least one of a cost data and a number data; number of treatment sessions, generate a treatment plan from at least one of the cost data and the number of treatment sessions data.

19. Method, according to any one of the preceding claims, characterized by the fact that the step of generating a treatment plan further comprises at least one of the following steps: generating and displaying the application stamps linked to the treatment plan, generating an application chain (CA) from the grouping of a set of application stamps linked to a given user, in which the application chain further comprises at least one of the treatment identification code and the treatment cost data.

20. Method according to any one of the preceding claims, characterized in that the application stamp is segmented into at least a first portion and a second portion, each portion comprising the same amount of data, wherein the treatment code data is outlined by an attention flag.

21. Method according to any one of the preceding claims, characterized in that it further comprises at least one of the following steps: sending at least one of the application seal and the application string to an automated applicator, and sending at least one of the application seal and the application string to a professional applicator.

22. Method according to any one of the preceding claims, characterized in that it further comprises at least one of the following steps: record the application of the application chain, whether said application is carried out by the automated applicator or by the professional applicator, and generate at least one recording data (DG), and store the recording data (DG) in the application chain (CA).

23. Method, according to claim 22, characterized by the fact that the treatment plan comprises at least one application action (AP1, AP2, AP3...APN), in which the method further comprises at least one among the following steps: generating the recording data (DG) for each application action (AP1, AP2, AP3...APN) existing in the treatment plan, generating the cost data (DC) for each application action (AP1, AP2, AP3...APN) existing in the treatment plan.

24. Method, according to any one of the preceding claims, characterized by the fact that it further comprises the steps of: generating a graphical representation of a professional, in which the graphical representation is generated by means of artificial intelligence, and conducting an interaction between the user and the computing platform, in which the interaction is conducted by the graphical representation generated by means of artificial intelligence.

25. Method according to any one of the preceding claims, characterized in that the graphical representation generated by means of artificial intelligence is a graphical representation of a medical professional (100) and / or a multidisciplinary graphical representation (200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100).

26. Method according to any one of the preceding claims, characterized in that the graphical representation multidisciplinary graphic representation (200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100) is configured as at least one of: a first multidisciplinary graphic representation (200) of a biomedical scientist, a second multidisciplinary graphic representation (300) of a professor, a third multidisciplinary graphic representation (400) of a nurse, a fourth multidisciplinary graphic representation (500) of a pharmacist, a fifth multidisciplinary graphic representation (600) of an accounting professional, a sixth multidisciplinary graphic representation (700) of a marketing professional, a seventh multidisciplinary graphic representation (800) of a product consultant, an eighth multidisciplinary graphic representation (900) of a business manager, a ninth multidisciplinary graphic representation (1000) of a digital influencer, and a tenth multidisciplinary graphic representation (1100) of a lawyer.

27. Method, according to any one of the preceding claims, characterized by the fact that it further comprises the step of: associating the treatment plan with an augmented reality environment, in which said step further comprises: generating a set of instructions (1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020 and 2100) linked to the application of the substance to the patient, in which the set of instructions (1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020 and 2100) is perceptible at least in an augmented reality environment and perceptible through the computational platform.

28. Method according to claim 27, characterized in that the set of instructions (1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020 and 2100) comprises at least one graphical instruction (1300, 1500, 1700, 1800, 2000, 2010, 2020), such that said graphical instruction (1300, 1500, 1700, 1800, 2000, 2010, 2020) is arranged in a superimposed manner on a representation of the patient.

29. Method according to claim 28, characterized in that the set of instructions (1300, 1310, 1500, 1700, 1800, 1710, 1810, 1900, 2000, 2010, 2020 and 2100) comprises at least one instruction (2000) configured as the virtual illustration of one of the application stamps (S1, S2...SN).

30. Computer system for obtaining a treatment plan related to a user, characterized by the fact that it comprises a computer platform (30) equipped with a processor, the processor capable of receiving a set of instructions that, when executed, carry out the steps of the method, as defined in claim 1.

31. Computer-readable memory containing a set of instructions that, when executed, perform the steps of the method as defined in claim 1.

32. Computing platform (30) comprising a processor, characterized in that the processor is capable of receiving a set of instructions that, when executed, perform the method as defined in claim 1.

33. Computational method for consultation, diagnostic evaluation and financial planning to generate a treatment plan. treatment related to a user, characterized by the fact that it comprises the steps of: receiving, on a computational platform, a plurality of general input data from a given user, generating a treatment identification code from the plurality of general input data, collecting a plurality of query data related to the user, scanning, on the computational platform, at least a portion of the user, and generating the treatment plan at least from the scanning of at least a portion of the user, and associating the treatment plan with an augmented reality device.

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