Systems and methods for analyzing hair and scalp health

Abstract

A system for determining one or more of a user's hair health and scalp health, the system including a hair analysis assembly configured to acquire a set of hair images of the user, analyze the set of hair images to detect one or more head characteristics, and calculate a set of head health scores for the user based on the one or more detected head characteristics, the system further capable of outputting the head health score for the user.

Description

[Technical Field]

[0001] The present invention relates to measuring and analyzing hair and scalp characteristics and health using a smartphone-mounted hair analysis device. [Background technology]

[0002] Hair and scalp care product manufacturers develop products to help users maintain healthy hair and scalp, but one of the biggest challenges is determining an accurate and useful score for hair and scalp so that appropriate product and treatment recommendations can be made.

[0003] Several solutions exist that attempt to provide accurate and useful analyses, but these solutions have numerous limitations and drawbacks. For example, some solutions suffer from measurement inaccuracies, user or environmental variability, high cost, expertise required to operate the solution and perform the analysis, and logistical challenges such as bulky hardware.

[0004] Therefore, there is a need in the art for improved methods and systems that can determine an accurate assessment or scoring of hair health and scalp health (hereinafter sometimes collectively referred to as "head health"). Summary of the Invention

[0005] A system for evaluating a user's head health, the system including a hair analysis assembly configured to receive an input to initiate capture of a first set of head images of a user, acquire the first set of head images, transmit the first set of head images to a trained artificial intelligence system, analyze the first set of head images for a first set of head health features, receive from the trained artificial intelligence system a first head health feature result set including a position and number of each of the first set of head health features in each image of the first set of head images of the user, apply a first set of head health rules to the first head health feature result set, create a first head health evaluation set based on the application, and report the first head health evaluation set.

[0006] The hair analysis assembly may include a mobile device and a hair analysis device removably attached to the mobile device.

[0007] The hair analysis assembly may be further configured to receive product recommendations based on the first head health assessment set and report the product recommendations.

[0008] The first set of head images may include a first set of hair images, and the first set of head health features may include a first set of hair health features.

[0009] The first set of hair health features may include thermal damage, mechanical damage and dryness.

[0010] The head health rules may include hair health rules, which include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features.

[0011] The first set of head images may include a first set of scalp images, and the first set of head health features may include a first set of scalp health features.

[0012] Primary characteristics of scalp health may include small scales, medium and large scale scales, flaky hair shafts, oily flaky scalp, sticky hair shafts, and buildup.

[0013] The head health rule may include a scalp health rule, and the scalp health rule may include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

[0014] The hair analysis device may further include cross-polarized light, and the acquiring may be performed with cross-polarized light for a first subset of the first set of scalp health features.

[0015] The first head image set may include a first hair image set and a first scalp image set, and the first head health feature set includes a first hair health feature set and a first scalp health feature set.

[0016] The first set of hair health features may include thermal damage, mechanical damage, and dryness, and the first set of scalp health features may include small flakes, medium and large flakes, flaky hair shaft, flaky scalp oil pooling, sticky hair shaft, and buildup.

[0017] The head health rules include hair health rules that may include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features, and scalp health rules that may include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

[0018] The acquiring may further include preparing a head image acquisition device for acquiring the head images and assessing head characteristics by configuring the device.

[0019] Also provided is a method for evaluating a user's head health, the method including receiving, by a hair analysis assembly, an input to initiate capture of a first set of head images of a user; acquiring the first set of head images by the hair analysis assembly; transmitting the first set of head images to a trained artificial intelligence system and analyzing the first set of head images for a first set of head health features; receiving, from the trained artificial intelligence system, by the hair analysis assembly, a first head health feature result set including a location and number of each of the first set of head health features in each image of the first set of head images of the user; applying a first set of head health rules to the first head health feature result set; creating a first head health evaluation set based on the application; and reporting the first head health evaluation set.

[0020] The first set of head images may include a first set of hair images, and the first set of head health features includes a first set of hair health features.

[0021] The first set of hair health features may include thermal damage, mechanical damage and dryness.

[0022] The head health rules may include hair health rules, and the hair health rules may include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features.

[0023] The first set of head images may include a first set of scalp images, and the first set of head health features may include a first set of scalp health features.

[0024] The first set of scalp health features may include small flakes, medium and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and buildup.

[0025] The head health rule may include a scalp health rule, and the scalp health rule may include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

[0026] The hair analysis device may further include cross-polarized light, and the obtaining may be performed with cross-polarized light for a first subset of the first set of scalp health features.

[0027] The first head image set may include a first hair image set and a first scalp image set, and the first head health feature set includes a first hair health feature set and a first scalp health feature set.

[0028] The first set of hair health features may include thermal damage, mechanical damage, and dryness, and the first set of scalp health features may include small flakes, medium and large flakes, flaky hair shaft, flaky scalp oil pooling, sticky hair shaft, and buildup.

[0029] The head health rules may include hair health rules that may include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features, and scalp health rules that may include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

[0030] The acquiring may further include preparing a head image acquisition device for acquiring the head images and assessing head characteristics by configuring the device.

[0031] A system for determining one or more of a user's hair health and scalp health, the system including a hair analysis assembly configured to acquire a set of hair images of the user, analyze the set of hair images to detect one or more head characteristics, and calculate a set of head health scores for the user based on the one or more detected head characteristics, the system further capable of outputting the head health score for the user.

[0032] The hair analysis assembly may include a mobile device and a hair analysis device that attaches to the mobile device.

[0033] The hair analysis device may further include cross-polarized light, the cross-polarized light being used to obtain at least one image of the user's head, and the analysis including at least one image of the user's head obtained using the cross-polarized light.

[0034] The head characteristics may include one or more of a set of hair characteristics, which may include thermal damage, mechanical damage, dryness, and scalp characteristics, which may include small flakes, medium and large flakes, flaky hair shafts, flaky scalp oil pooling, sticky hair shafts, and buildup.

[0035] The calculation may further be based on one or more hair analysis rules and scalp analysis rules.

[0036] The user's set of head health scores may include one or more hair scores and one or more scalp scores.

[0037] The hair analysis assembly may be further configured to provide product recommendations based on the user's head health score.

[0038] Also provided is a method for determining one or more of a user's hair health and scalp health, the method including: obtaining a set of head images of the user from a hair analysis assembly; analyzing the set of head images of the user to detect one or more head characteristics; calculating a set of head health scores for the user based on the one or more detected head characteristics; and outputting the head health score for the user.

[0039] The hair analysis assembly may include a mobile device and a hair analysis device that attaches to the mobile device.

[0040] The hair analysis device may further include cross-polarized light, the cross-polarized light being used to obtain at least one image of the user's head, and the analysis including at least one image of the user's head obtained using the cross-polarized light.

[0041] The head characteristics may include one or more of a set of hair characteristics, which may include thermal damage, mechanical damage, dryness, and scalp characteristics, which may include small flakes, medium and large flakes, flaky hair shafts, flaky scalp oil pooling, sticky hair shafts, and buildup.

[0042] The calculation may further be based on one or more hair analysis rules and scalp analysis rules.

[0043] The user's set of head health scores may include one or more hair scores and one or more scalp scores.

[0044] The method may further include providing product recommendations based on the user's head health score. [Brief explanation of the drawings]

[0045] The present invention is illustrated in the figures of the accompanying drawings, which are intended to be illustrative and not limiting, and in which like references are intended to refer to like or corresponding parts: [Figure 1] FIG. 1 depicts an embodiment of a hair analysis system according to one embodiment of the present invention; [Figure 2] FIG. 2 is a method of determining hair health using a hair analysis system according to an embodiment of the present invention; [Figure 3] 3a-d are exemplary screenshots of an application embodying aspects of the present invention; [Figure 4] 4a-c are hair images showing exemplary features to aid in the assessment of hair health; [Figure 5] 5a-g are scalp images showing exemplary features to aid in the assessment of scalp health; [Figure 6] Figure 6 is a hair image showing exemplary feature identification for assessing hair health; [Figure 7] FIG. 7 is a hair image illustrating exemplary feature identification for assessing hair health. Detailed Description of the Invention

[0046] System 100 generally includes a hair analysis assembly 104 ("HAA," which may include a hair analysis device 108 (scanner) preferably removably attached to a mobile device 106) that, when used by a user 102, performs one or more hair analysis operations, such as capturing images for color assessment of the user's hair or face, as described herein.

[0047] The HAA 104 may be as described in PCT / CA2020 / 050216 or PCT / CA2017 / 050503, or may include another hair analysis system capable of capturing images of the user's head, said images having sufficient characteristics for the analysis described herein. It is understood that the hair analysis assembly 104 may have a hardware configuration similar to that described in these documents and may operate and function similarly as described in these documents. The HAA may also include applications (apps) that the user 102 can use to enable, control, or review the methods described herein.

[0048] In particular, as mentioned above, system 100 requires the ability to acquire head images (hair and / or scalp images) that enable the processing described herein. In one embodiment, the head images may be captured using a 10 megapixel camera at 10x or greater magnification with cross-polarized light or while cross-polarized light is "on" (e.g., to remove glare or reflections of light sources from the head image).

[0049] The user's head image may be in one of several color formats, such as LAB or RGB. The user's head image may be of virtually any quality, type, format, or size / file size, so long as the methods herein are applicable. For example, the image may be compressed or uncompressed, raw or processed, and in a variety of file formats.

[0050] The hair analysis server (HAS) 110 may be a server that stores and processes hair characteristic measurements or samples as described herein. The HAS 110 may be any combination of a web server, an application server, and a database server, as known to those skilled in the art. Each such server may include a typical server configuration, including a processor, volatile and non-volatile memory storage, and software instructions executable thereon. The HAS 110 may communicate via an app 18 to perform the functions described herein, including exchanging head images, product recommendations, e-commerce functions, etc. Of course, the app may perform these functions alone or in combination with the HAS 110.

[0051] The HAS 110 may include a data server that receives and stores all head characteristic samples from all users in a user profile for each registered user 102 and guest user 102. These may be received from one or more HAAs 104, although the app may be configured to only store head images locally (although this may exclude some of the outcome information based on population and attribute comparisons).

[0052] HAS 110 may provide various analytical functions as described herein (e.g., calculating histograms of comparisons to a user's past results or comparisons to peers) and may provide various display functions as described herein (e.g., providing a website that can display various analyses and provide links or functional links to other websites for accessing and displaying such results, recommendations, etc.).

[0053] The product owner 120 may be, for example, an entity that has hair and scalp care products that can or should be adapted or selected based on a user's head. The product owner 120 may also have one or more product owner servers, including a web server, an application server, and a database server, as known to those skilled in the art. Each such server may include a typical server configuration, including a processor, volatile and non-volatile memory storage, and software executable thereon. The product owner 120 may be a communication point for the app 18 (directly or via the HAS 110) for hair analysis measurement samples (such as those obtained via a user provided with a hair analysis device 20 by such product owner 120) and for storing and executing product recommendation algorithms. For example, one or more generic product recommendation algorithms may be stored and owned by the HAS 110 for each product recommendation type, or the product owner may own and implement their own product recommendation algorithm (e.g., the product owner 120 receives the data necessary to run the product recommendation algorithm and returns recommended products).

[0054] Product Owner 120 provides e-commerce services directly and through Amazon TM The product owner 120 may also suggest (separately or in conjunction with the recommended products) other business partners (not shown) or may be agnostic to the method by which the user purchases the recommended products. The product owner 120 may also provide one or more e-commerce websites or screens (separate or incorporated with the app) that facilitate business or commercial transactions, including the transfer of information over a network 130 (e.g., the Internet). Types of e-commerce sites include, but are not limited to, retail sites, auction sites, and business-to-business sites. Exemplary businesses that facilitate the purchase of head care products include Amazon. TM , eBay TM , and Overstock TMOf course, the product owner 120 may have its own e-commerce site as part of a general website, or the HAS 110 may be such an operator.

[0055] The system 102 may include other users 102, such as a product owner 120 or a beauty advisor or consultant working at a trading site or store, who assist the user 102 who is the subject of the image and whose head health condition is being determined.

[0056] Turning to FIG. 2, a method 200 for determining and treating the health of the head (hair and / or scalp) is shown.

[0057] The method 200 begins at 202 with pairing.

[0058] The hair analysis device 108 may have an SDK that apps on the mobile device 104 can use to access the functionality of the HAD 108. The SDK may provide methods for discovering, pairing, and controlling the scanner.

[0059] On initial launch of the app, it is recommended that it explores, discovers, and displays all scanners within range (using the scan For Devices method). If after a discovery session only one scanner is discovered, consider automatically initiating pairing (connect To Device method) without displaying a list of discovered scanners. See Figure 3a.

[0060] After successful pairing, for a better user experience, you may want to save the ID of the paired device, and then each time you launch the app, it will automatically reconnect to that device without having to repeat the pairing procedure.

[0061] The SDK will automatically disconnect from the scanner when the app is terminated or leaves an active state (smartphone goes to sleep or the app goes to background). When the app returns to the foreground, the SDK can reconnect to the paired scanner. When performing scanner-related operations, apps should always check whether a valid connection is available. Such verification may be part of the pairing in 202.

[0062] The method 200 continues with performing alignment 204. This may be omitted if the scanner is removably attached to the mobile device to ensure proper alignment.

[0063] For clip-on scanner models, the SDK can provide helper methods to guide the user in scanner positioning. The scanner needs to be clipped to the correct camera lens and accurately centered to eliminate optical distortions and obscurations. The start Lens Positioning Validation method can be used to start tracking the scanner's position. This method provides constant status updates on the alignment information. After the alignment is confirmed by the user, the end Lens Positioning Validation method should be called to stop the alignment status updates. When viewing the camera's live view, it is useful to turn on the LED white light. See Figure 3b.

[0064] At 206 and 208, one or more head health assessments or head health scans are initiated and performed to obtain one or more sets of head images.

[0065] The Scanner SDK provides the takeScalpPhoto method to initiate a capture of a user's scalp. This method is typically invoked by a button click or other user input, allowing the user to position the scanner on their scalp (their own or their client's). It is also recommended to display a live view of the camera as well. See Figure 3c for an example of a live view configured for scalp image capture.

[0066] The Scanner SDK provides a takeHairPhoto method to initiate the capture of a user's hair. This method is typically initiated by a button click, allowing the user to position the scanner at the end of a hair (their own or the client's). It is also recommended to display a live view of the camera as well. See Figure 3d for an example of a live view configured for hair image capture.

[0067] The initiation of scalp image capture and hair image capture typically do not occur simultaneously due to different focal lengths for each head image capture (hair image capture and scalp image capture). Therefore, as part of 206 and / or 208, the HAA may prepare for the particular head image capture to be initiated (e.g., set the appropriate focal length, turn on the appropriate lighting, adjust the appropriate magnification, etc., i.e., establish performance settings applicable to the type of head image—hair or scalp—and head characteristics—hair characteristics or scalp characteristics). However, the capture of the hair image set and scalp image set may occur in any order.

[0068] Furthermore, capturing each head image may involve capturing one or more images using one or more scanner functions. For example, different lighting, flash, and camera components / settings (e.g., magnification, focal length, illumination used) may be used. Each combination of performance settings may be referred to as a function setting and may be associated with a particular type of head image being captured and the head characteristics being evaluated. As discussed further, cross-polarized light may be used in capturing one scalp image (e.g., to help identify certain features detected to assess scalp health, i.e., scalp flakes and flaky hair shafts). It should be understood that the scope of the present invention includes various combinations of images captured with various setting combinations, depending on the health characteristics desired to be detected, the usability, scanner hardware, etc.

[0069] Image analysis is performed at 210 and includes a hair health analysis (analyzing one or more images of the user's hair as described herein) and a scalp health analysis (analyzing one or more images of the user's scalp as described herein).

[0070] The analysis can be performed by providing an appropriate user's head image to an artificial intelligence system (e.g., the popular object detection ML model YOLOv2) trained to identify one or more hair health features and / or scalp health features (hair health features and scalp health features are examples of head health features). Such an AI system can review the image and identify the location and number of occurrences of hair health features (described herein in head images 600 (hair image) and 700 (scalp image)) as shown in FIGS. 6 and 7. After identifying the head health features, various head health rules (hair health rules and scalp health rules) can be applied to arrive at a head health assessment, such as a hair health assessment / score and a scalp health assessment / score, as described herein. The trained artificial intelligence system can be located locally (e.g., on a mobile device) or remote from the hair analysis assembly 104.

[0071] Exemplary hair health characteristics and rules and / or scalp health characteristics and rules are described below, although others are possible. Hair health analysis (split ends) and hair health characteristics / properties

[0072] The process and output detects the characteristics / characteristics (frequency or number, location, and size or severity) of thermal damage (see Figure 4a - can be caused by exposure of hair to high temperatures such as hair dryers and straighteners, causing hair to lose elasticity and become more susceptible to damage), mechanical damage (see Figure 4b - can be caused by improperly used detangling techniques, tension, and over-manipulation, causing hair to thin at the ends, resulting in tangles, excessive split ends, and breakage), and dryness (see Figure 4c - can be caused by dry weather and frequent washing with too hot water, or lack of thermal protection due to hair dryers and straighteners, causing dry hair to become brittle, thereby causing split ends at the ends). The algorithm can output a damage rating (user's hair score) for thermal, mechanical, dry (or a combination thereof), or none, according to one or more configurable rating rules.

[0073] Exemplary hair analysis or evaluation rules include the following: (a) If the number of feature detections for "thermal damage" exceeds 4 (or other configurable number / threshold), thermal damage is selected as the final analytical evaluation; otherwise (b) If the number of feature detections for "mechanical damage" exceeds 4 (or other configurable number / threshold), mechanical damage is selected as the final analytical evaluation; otherwise (c) If the number of detections of the "dry" feature exceeds 4 (or other configurable number / threshold), dry damage is selected as the final analytical assessment; otherwise (d) None.

[0074] It should be understood that each of the above values ​​(e.g., times greater than "4") are configurable and can be changed based on parameters establishing what constitutes a particular feature detection. Other evaluation rules may also be selected, for example, by running the system to identify damage and basing the rules on observed results (whether human or machine driven).

[0075] It should further be understood that various features (hair and / or scalp) and combinations of features (hair and / or scalp) may be evaluated for any given set of head images, and some or all of the selected features may be used in various rules that may be used to make one or more evaluations. In one embodiment, thermal damage, mechanical damage, and dryness are all features for which hair images are analyzed and are all factors in the rules for evaluating hair health, although various permutations and combinations are possible. Scalp health analysis and scalp health characteristics

[0076] The processing and output can be divided into small flakes (see Figure 5a - preferably using cross-polarized images, where small flakes are small pieces of dead scalp skin generally 1 mm in diameter or less, and are indicative of scalp dryness), medium and large flakes (see Figure 5b - using cross-polarized images, where medium and large flakes are small pieces of dead scalp skin greater than 1 mm in diameter, and are processed separately from small flakes, as small flakes tend to indicate scalp dryness, while medium and large flakes tend to indicate dandruff), and flaky hair shafts (see Figure 5c - Preferably using cross-polarized images. Here, flaky hair shafts are unhealthy hair shafts covered with small, dead scalp skin flakes, which indicate scalp dryness and are individually identifiable by AI tools, and therefore used separately from other flake types.), flaky scalp (see Figure 5d - preferably using cross-polarized images. Here, flaky scalp skin is small, dead scalp skin flakes that are still partially attached to the scalp and are in the process of becoming larger flakes. Like flaky hair shafts, this morphology is primarily translucent and not attached to the hair shaft. These have their own visual characteristics and may therefore require to be treated as distinct features by the ML model.), oil puddle (see Figure 5e - preferably without cross-polarized images. Here, oil puddle is a scalp condition when excess oil accumulates around the hair shaft. It can be described as a semi-transparent circular shape around the hair shaft. The presence or absence of these features indicates an oily scalp.), sticky hair shaft (see Figure 5f - preferably without cross-polarized images. Sticky hair shaft is an oily scalp condition that shows extreme excess oil around the hair shaft. Detect the characteristics / traits (frequency or number, location and size or severity) of buildup (see Figure 5g - without cross-polarized imagery, where buildup can be caused by both excess oil and dry scalp, or in rare cases, product residue). Buildup is visually similar to "sticky hair shaft" but can be distinguished because it is usually not translucent and typically has small particles around the hair shaft.)The algorithm can output a damage rating of greasiness, buildup, flaking or normal according to one or more configurable rating rules.

[0077] Typical scalp assessment or analysis rules include: (a) If the feature detection count of "oil pool" + "sticky hair shaft" is 4 or more, oily damage is selected as the final analytical evaluation; otherwise (b) If the feature detection count of "accumulation" is 2 or more and the "sum of all flake detections" ("small flakes" + "medium and large flakes" + "flaky hair shaft" + "flaky scalp") is below the count of "accumulation" multiplied by 5, then the accumulation is selected; otherwise (c) If the feature detection count of "sum of all flake detections" ("small flakes" + "medium and large flakes" + "flaky hair shaft" + "flaky scalp") is greater than 4 or "flaky scalp" is greater than 1, flakes are selected; otherwise (d) None.

[0078] It should be understood that each of the above values ​​(e.g., times greater than "4") are configurable and can be changed based on parameters establishing what constitutes a particular feature detection. Other evaluation rules may also be selected, for example, by running the system to identify damage and basing the rules on observed results (whether human or machine driven).

[0079] It should further be understood that various features (hair and / or scalp) and combinations of features (hair and / or scalp) may be evaluated for any given set of head images, and some or all of the selected features may be used in various rules that may be used to make one or more assessments. In one embodiment, oil pools, sticky hair shafts, small flakes, medium and large flakes, flaky hair shafts, and flaky scalp are all features for which scalp images are analyzed and are all factors in the rules for assessing scalp health, although various permutations and combinations are possible.

[0080] The head health assessment and head health assessment data (including the underlying user's head image, the processed user's head image displaying detected features, the scoring, and the assessment) may be reported or stored at 212 (e.g., displayed on the mobile device, sent to cloud storage such as the product owner 120 or the hair analysis server 110, etc.). In addition to reporting and storing, the user may be provided with one or more head health product recommendations to address the head health assessment. Recommendations may be made based on the product user's knowledge of how their products affect head health features and the user's answers to questions about their own experiences and goals.

[0081] The embodiments of the present disclosure described above can be implemented in any of numerous ways. For example, the embodiments can be implemented using hardware, software, or a combination thereof. If implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided on a single computer or distributed across multiple computers.

[0082] Additionally, the various methods or processes outlined herein may be coded as software executable on one or more processors employing any one of a variety of operating systems or platforms, and such software may be written using any of a number of suitable programming languages ​​and / or programming or scripting tools, and may be compiled as executable machine language code or intermediate code that runs on a framework or virtual machine.

[0083] In this regard, the concepts disclosed herein may be embodied as a non-transitory computer-readable medium (or media) (e.g., computer memory, one or more floppy disks, compact disks, optical disks, magnetic tapes, flash memory, circuitry in a field programmable gate array or other semiconductor device, or other non-transitory tangible computer storage medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the present disclosure described above. The computer-readable medium or media may be portable, and the program or programs stored thereon may be loaded onto one or more different computers or other processors to implement various aspects of the present disclosure, as described above.

[0084] As used herein, the terms "program," "app," "application," or "software" are used to refer to any type of computer code or collection of computer-executable instructions that may be employed to program a computer or other processor to implement various aspects of the present disclosure, as described above. Furthermore, it should be noted that, in accordance with one aspect of the present embodiment, one or more computer programs that perform the methods of the present disclosure need not reside on a single computer or processor, but may be distributed in the form of modules among multiple different computers or processors to implement various aspects of the present disclosure.

[0085] Computer-executable instructions may exist in many forms, such as program modules executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0086] Additionally, data structures may be stored on computer-readable media in any suitable form. For ease of illustration, data structures may be shown as having fields that are related via location within the data structure. Such relationships may similarly be achieved by allocating storage to the fields with locations within the computer-readable media that convey the relationship between the fields. However, any suitable mechanism may be used to establish relationships between information within fields of a data structure, including the use of pointers, tags, or other mechanisms that establish relationships between data elements.

[0087] Various features and aspects of the present disclosure may be used alone, in combination of two or more, or in various arrangements not specifically described in the previously described embodiments, and therefore, its application is not limited to the details and arrangements of construction set forth in the foregoing description or drawings. For example, aspects described in one embodiment may be combined in any manner with aspects described in other embodiments.

[0088] Additionally, the concepts disclosed herein may be implemented as a method, an example of which is shown. The acts performed as part of the method may be reordered in any suitable manner. Thus, embodiments may comprise operations performed in an order different from that shown, and may include performing some operations simultaneously, even if shown as sequential in the illustrated embodiments.

[0089] The use of ordinal terms such as "first," "second," "third," etc. in the claims to modify claim elements does not, by itself, imply any priority, precedence, or ordering of one claim element relative to another or chronological order of method acts performed, but is merely used as a label to distinguish a claim element having a certain name from other elements having the same name (except for the use of ordinal terms).

[0090] Also, the phrases and terms used herein are for purposes of description and should not be regarded as limiting. As used herein, the use of "including," "comprising," "having," "containing," "involving," and variations thereof, is meant to include the items listed thereafter and equivalents of additional items.

[0091] Some (or different) elements below and / or in the claims may be described as being "coupled," "in communication," or "configured to communicate." This term is intended to be non-limiting and is to be interpreted to include, without limitation, wired and wireless communications, where appropriate, using any one or more suitable protocols, as well as communication methods that are constantly maintained, periodically performed, and / or performed or initiated on an as-needed basis.

[0092] Embodiments may also be implemented in a cloud computing environment. For purposes of this specification and the following claims, "cloud computing" may be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) that can be rapidly provisioned through virtualization, released with minimal management effort or service provider interaction, and then scaled accordingly. The cloud model may be comprised of a variety of characteristics (e.g., on-demand self-service, pervasive network access, resource pooling, rapid elasticity, metered service), service models (e.g., Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS)), and deployment models (e.g., private cloud, community cloud, public cloud, hybrid cloud).

[0093] This description uses examples to disclose the invention and will enable any person skilled in the art to make and use the invention. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements that do not differ substantially from the literal language of the claims.

[0094] It should be understood that the above-described assemblies and modules can be interconnected as needed to perform the desired functions and tasks, to the extent that such combinations and permutations are possible by one skilled in the art without explicitly describing each one. No particular assembly or component is superior to any of the equivalents available to those skilled in the art. No particular mode of performing the disclosed subject matter is superior to other modes, so long as the function can be performed. All important aspects of the disclosed subject matter are believed to have been provided herein. The scope of the present invention is understood to be limited to the scope provided by the independent claims, and is not limited to: (i) the dependent claims, (ii) the detailed description of non-limiting embodiments, (iii) the summary, (iv) the abstract, and / or (v) any description provided outside this specification (i.e., outside this application as filed, prosecuted, and / or patented). In this specification, the term "includes" is understood to be equivalent to the term "comprising." The above outlines non-limiting embodiments (examples). The non-limiting embodiments should be understood to be merely illustrative by way of example.

Claims

1. A user head health evaluation system, comprising: The system includes a hair analysis assembly; The hair analysis assembly comprises: receiving a user input to initiate capture of a first set of head images; acquiring the first set of head images; transmitting the first set of head images to a trained artificial intelligence system and analyzing the first set of head images for a first set of head health features; receiving a first set of head health feature results from the trained artificial intelligence system, the first set of head health features including a location and a number of each of the first set of head health features in each image of the first set of head images of the user; applying a first set of head health rules to the first set of head health feature results; creating a first head health assessment set based on the application; and, and configured to report the first set of head health assessments.

2. 10. The system of claim 1, wherein the hair analysis assembly includes a mobile device and a hair analysis device removably attached to the mobile device.

3. 10. The system of claim 1, wherein the hair analysis assembly is further configured to receive product recommendations based on the first head health assessment set and report the product recommendations.

4. The system of claim 1 , wherein the first set of head images includes a first set of hair images, and the first set of head health features includes a first set of hair health features.

5. 5. The system of claim 4, wherein the first set of hair health features includes thermal damage, mechanical damage, and dryness.

6. 6. The system of claim 5, wherein the head health rules include hair health rules, and the hair health rules include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features.

7. The system of claim 1 , wherein the first set of head images includes a first set of scalp images, and the first set of head health features includes a first set of scalp health features.

8. 8. The system of claim 7, wherein the first scalp health set includes small flakes, medium and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and buildup.

9. 9. The system of claim 8, wherein the head health rules include scalp health rules, and the scalp health rules include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

10. 10. The system of claim 9, wherein the hair analysis device further comprises cross-polarized light, and wherein the acquisition is performed with cross-polarized light for a first subset of the first set of scalp health features.

11. 2. The system of claim 1, wherein the first set of head images includes a first set of hair images and a first set of scalp images, and the first set of head health features includes a first set of hair health features and a first set of scalp health features.

12. 12. The system of claim 11, wherein the first set of hair health features includes thermal damage, mechanical damage, and dryness, and the first set of scalp health features includes small flakes, medium and large flakes, flaky hair shaft, flaky scalp oil pooling, sticky hair shaft, and buildup.

13. 13. The system according to claim 12, wherein the head health rule comprises: hair health rules, comprising comparing the number of each of the first set of hair health features in the hair image to a configurable threshold for each of the first set of hair health features; and a scalp health rule that includes comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

14. 14. The system of claim 13, wherein said acquiring further comprises preparing a head image acquisition device for acquiring said head images and assessing head characteristics by configuring the device.

15. A method for evaluating a user's head health, comprising: The method comprises: receiving, by a hair analysis assembly, an input to initiate capture of a first set of images of the user's head; acquiring the first set of head images with the hair analysis assembly; transmitting the first set of head images to a trained artificial intelligence system and analyzing the first set of head images for a first set of head health features; receiving, by the hair analysis assembly from the trained artificial intelligence system, a first set of head health feature results including a location and a number of each of the first set of head health features in each image of the first set of head images of the user; applying a first set of head health rules to the first set of head health feature results; generating a first hair health assessment set based on said application; and reporting said first set of hair health assessments.

16. 16. The method of claim 15, wherein the first set of head images comprises a first set of hair images, and the first set of head health features comprises a first set of hair health features.

17. 17. The method of claim 16, wherein the first set of hair health features includes thermal damage, mechanical damage, and dryness.

18. 18. The method of claim 17, wherein the head health rules include hair health rules, and the hair health rules include comparing the number of each of the first set of hair health features in the hair image with a configurable threshold for each of the first set of hair health features.

19. 16. The method of claim 15, wherein the first set of head images includes a first set of scalp images, and the first set of head health features includes a first set of scalp health features.

20. 20. The method of claim 19, wherein the first set of scalp health features includes small flakes, medium and large flakes, flaky hair shafts, flaky scalp oil pools, sticky hair shafts, and buildup.

21. 21. The method of claim 20, wherein the head health rules include scalp health rules, and the scalp health rules include comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

22. 22. The method of claim 21, wherein the hair analysis device further comprises cross-polarized light, and wherein the acquiring is performed with cross-polarized light for a first subset of the first set of scalp health features.

23. 16. The method of claim 15, wherein the first set of head images includes a first set of hair images and a first set of scalp images, and the first set of head health features includes a first set of hair health features and a first set of scalp health features.

24. 24. The method of claim 23, wherein the first set of hair health features includes thermal damage, mechanical damage, and dryness, and the first set of scalp health features includes small scale, medium and large scale, flaky hair shaft, flaky scalp oil pool, sticky hair shaft, and buildup.

25. 25. The method of claim 24, wherein the head health rule comprises: hair health rules, comprising comparing the number of each of the first set of hair health features in the hair image to a configurable threshold for each of the first set of hair health features; and a scalp health rule that includes comparing the number of each of the first set of scalp health features in the scalp image with a configurable threshold for each of the first set of scalp health features.

26. 26. The method of claim 25, wherein said acquiring further comprises preparing a head image acquisition device for acquiring said head images and assessing head characteristics by configuring the device.

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