System and method for comprehensive scalp health evaluation using non-invasive imaging techniques

Abstract

The invention provides a system and method for scalp health evaluation using non invasive imaging techniques. This data is mapped to specific scalp regions and analyzed using AI to diagnose conditions and provide personalized treatment recommendations. The system enables real-time monitoring of individual hair follicles over time and generates visual representations such as heat maps and 3D models for improved diagnosis and care.

Description

[0001] System and Method for Comprehensive Scalp Health Evaluation Using Non- Invasive Imaging Techniques

[0002] The invention provides a system and method for scalp health evaluation using non- invasive imaging techniques. This data is mapped to specific scalp regions and analyzed using Al to diagnose conditions and provide personalized treatment recommendations. The system enables real-time monitoring of individual hair follicles over time and generates visual representations such as heat maps and 3D models for improved diagnosis and care.

[0003] Background of the Invention

[0004] In recent years, there has been a growing trend towards personalized solutions and recommendations in the beauty and care industry, driven by consumer demand for tailored products that address individual needs. Advancements in data-driven technologies, such as artificial intelligence (Al) and non-invasive imaging, have enabled companies to offer more targeted solutions based on the unique characteristics of each user. This shift reflects a broader trend in health and beauty, where one-size-fits-all approaches are being replaced by highly customized regimens designed to improve overall care outcomes.

[0005] Hair plays a crucial role in personal appearance, and healthy-looking hair is often viewed as a reflection of an individual’s vitality and well-being. The global beauty industry continues to prioritize innovations that enhance hair care, recognizing the importance of maintaining strong, shiny, and voluminous hair. However, healthy hair is deeply interconnected with the condition of the scalp, which serves as the foundation for hair growth and health. Issues like scalp dryness, excessive oil production, inflammation, and poor follicle health can significantly affect hair appearance and lead to concerns such as hair thinning or loss.

[0006] The human scalp contains an estimated 100,000 to 150,000 hair follicles, each of which progresses through distinct stages of growth, resting, and shedding throughout a person’s lifetime. These stages include the anagen phase (active growth), the catagen phase (transition), and the telogen phase (resting and shedding). As individuals age, hair follicles gradually transition through these phases with reduced efficiency, often leading to hair thinning, loss of density, or a complete cessation of hair growth in certain areas.

[0007] As a result, there is an increasing focus on scalp health in the hair care market. Maintaining an optimal scalp environment is essential for promoting stronger, healthier hair, and effective scalp care requires a detailed understanding of individual scalp conditions. This has led to the development of personalized scalp care systems, which leverage non-invasive technologies to assess scalp characteristics such as hydration levels, sebum production, hair follicle density, and microbiome balance. Through the integration of Al-driven analysis, these systems provide tailored recommendations for scalp and hair treatments, ensuring that care regimens are customized to meet the specific needs of each individual.

[0008] Therefore, there is a clear need to provide an accurate and detailed method for evaluating the scalp. Utilizing non-invasive imaging techniques offers an effective solution for capturing real-time data on various scalp and hair follicle characteristics, such as pore size, sebum production, hair follicle density, and scalp hydration levels. These technologies allow for comprehensive and personalized assessments, enabling early detection of issues and facilitating tailored treatments to address specific scalp conditions before they become more severe.

[0009] Hence, it is an object of the presently claimed invention to provide a method for diagnosing the state of the scalp which allows for accurate monitoring of hair follicles at a highly detailed level, utilizing non-invasive imaging techniques to observe changes in hair follicle characteristics, in the hair follicle environment, and / or of the scalp condition over time.

[0010] Summary of the invention

[0011] Surprisingly, it was found that by mapping the scalp and measuring the scalp characteristics using non-invasive technologies, a method is provided that allows for accurate monitoring of hair follicles. This method enables detailed tracking of changes in hair follicle characteristics, the hair follicle environment, and the overall scalp condition over time.

[0012] Hence, in one aspect the presently claimed invention is directed to a method for diagnosing the state of the scalp comprising at least the steps of: a) dividing a scalp into a plurality of coordinates to create a scalp map, wherein each coordinate corresponds to the surface of the scalp; b) evaluating at least one of the plurality of coordinates for at least one scalp characteristic in each coordinate to obtain a measured scalp characteristic; c) attributing the measured scalp characteristics to the plurality of coordinates on the scalp map; d) generating a visual image of the scalp based on the measured scalp characteristics and the plurality of coordinates, providing a comprehensive view of the scalp’s characteristics across different coordinates; e) diagnosing the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics, and identifying a deficiency and / or medical condition; optionally f) displaying the state of the scalp in an accessible format, and providing recommendations.

[0013] In another aspect, the presently claimed invention is directed to a system for diagnosing the state of the scalp comprising at least one device for evaluating at least one scalp characteristic using non-invasive imaging techniques, at least one computer for attributing the measured scalp characteristics to the corresponding coordinates, at least one database for storing the information related to the scalp characteristics and the plurality of coordinates, and at least one imaging unit capable of generating a visual image of the scalp based on the measured characteristics and the scalp map coordinates.

[0014] Detailed Description

[0015] In a preferred embodiment, the coordinates refer to specific points on the scalp that are mapped systematically to cover the entire surface area. Each coordinate corresponds to a precise location on the scalp, allowing for accurate evaluation of scalp characteristics such as hair density, oiliness, dryness, or any other relevant condition. These coordinates act as reference points for analysis, ensuring that scalp conditions are assessed consistently across different regions, facilitating a comprehensive understanding of the scalp’s health.

[0016] In a preferred embodiment, the scalp is divided into a plurality of coordinates using a system that segments the entire scalp surface into smaller, manageable areas. This segmentation can be achieved through methods such as applying a grid system that is dynamically tailored to the individual’s scalp dimensions and contours. The grid system adjusts to the scalp’s natural shape and topography, ensuring that each coordinate precisely covers an appropriate portion of the scalp’s surface. This allows for detailed and accurate scalp analysis, ensuring that no area is left unchecked, as the contours of the scalp are taken into account.

[0017] In a preferred embodiment, these coordinates are often based on a systematic mapping of the scalp surface using a proportional coordinate system (CPC) or similar method. Such systems allow for precise localization of specific points on the scalp by dividing the surface into a grid, employing anatomical landmarks as reference points. The coordinates may be represented in either Cartesian or spherical formats, facilitating accurate mapping of each point relative to the entire scalp area. This ensures high precision in the localization of specific areas, which is critical for applications including dermatological assessments, medical imaging, and electroencephalogram (EEG) localization. In a preferred embodiment, the use of advanced technologies, such as magnetic digitization or optical scanning, allows for submillimeter accuracy in determining the coordinates of scalp points. This accuracy enables reliable alignment of external scalp features with underlying anatomical structures, such as the brain, blood vessels, or muscle tissue. The coordinates may be stored digitally and utilized for repeated reference, ensuring consistency in applications that require precise targeting, such as therapeutic interventions or clinical diagnostics.

[0018] Further, in this embodiment, the coordinates may be adjusted to account for individual variations in scalp shape and size, enabling a customized mapping process that adapts to the unique contours of each subject's head. The system may incorporate algorithms for dynamic recalibration, allowing for real-time adjustments based on factors such as head movement or changes in posture. This ensures that the coordinates maintain their accuracy and relevance across different conditions and procedures.

[0019] In a preferred embodiment, the plurality of coordinates is categorized based on distinct scalp regions. These regions include, but are not limited to, the frontal-parietal zone, temporal-lateral zones, upper, middle, and lower occipital zones, crown, and vertex. This regional division ensures that all key areas of the scalp are covered, allowing for a thorough analysis of specific conditions in each zone, such as localized scalp dryness, sensitivity, or excessive sebum production.

[0020] In a preferred embodiment, the scalp is divided into several distinct zones for systematic assessment and mapping. These zones include the frontal-parietal zone, which spans from the forehead towards the crown of the head and plays a significant role in evaluating both scalp tension and hairline recession. The temporal-lateral zones are located on the sides of the head, adjacent to the temples and ears, and are commonly associated with the assessment of hair thinning and the condition of the scalp in high-friction areas.

[0021] The upper, middle, and lower occipital zones refer to the scalp regions at the back of the head, extending from the base of the skull upwards. The upper occipital zone connects to the crown, while the lower occipital zone lies closer to the neck. These areas are crucial for evaluating hair density and hair growth patterns. The crown (or vertex transition) marks the highest point of the head and is frequently evaluated in hair loss studies, given its susceptibility to androgenic alopecia. The vertex, often synonymous with the crown, specifically refers to the topmost point of the scalp, where hair loss may first become noticeable. These distinct zones provide a comprehensive framework for examining scalp health, hair density, and related conditions systematically.

[0022] In a preferred embodiment, each coordinate corresponds to a specific portion of the scalp’s surface. By mapping these coordinates onto the scalp, the system evaluates scalp characteristics at precise locations, facilitating the identification of scalp health variations. This approach enables the detection of conditions such as localized irritation or dryness, as well as the accurate assessment of factors like scalp elasticity or redness in defined regions. The mapping system not only aids in the analysis of current scalp conditions but also provides a reference point for monitoring changes over time.

[0023] In a preferred embodiment, the scalp map is generated by combining the coordinates with evaluation data collected from the scalp’s surface. Once the scalp is divided into a grid or set of coordinates, each coordinate is evaluated for characteristics such as dryness, sensitivity, dandruff, or oiliness. This data is used to create a visual representation, or scalp map, showing the distribution of these characteristics across the scalp, allowing for a comprehensive understanding of the scalp’s health condition. This visual map is essential for detecting patterns and diagnosing specific scalp issues that may require targeted treatment.

[0024] In a preferred embodiment, the coordinates are located in distinct scalp regions, such as the frontal-parietal zone, temporal-lateral zones, and occipital areas. These regions are crucial for accurate diagnosis because they represent areas where scalp conditions such as hair thinning or excessive oil production may vary significantly. By associating the coordinates with these specific regions, the method ensures a targeted and effective analysis of each zone’s condition, providing insights into how environmental or genetic factors may affect different parts of the scalp. In a preferred embodiment, the grid system, is customized to the individual’s scalp dimensions and contours. This customization is essential because the shape and size of each person’s scalp can differ, affecting how scalp conditions manifest. The grid system adjusts to these individual factors, ensuring that each coordinate accurately reflects a real portion of the scalp’s surface. This personalized grid system allows for precise evaluation and diagnosis, aligning closely with the natural topography of the individual’s scalp. For instance, in regions where the scalp’s curvature is more pronounced, the grid system compensates for this, ensuring that the scalp analysis remains accurate.

[0025] In a preferred embodiment, step a) involves dividing the scalp into a set of coordinates through a grid system tailored to individual scalp dimensions. This ensures that each coordinate corresponds to a specific part of the scalp. The system is critical for generating a comprehensive scalp map that allows for targeted evaluation of scalp conditions across different regions, providing accurate diagnosis and personalized treatment recommendations. Furthermore, the system can adapt to different diagnostic tools, integrating both visual and microscopic data to refine the analysis of scalp health.

[0026] In a preferred embodiment, the “evaluating” in step b) refers to analyzing at least one scalp characteristic at at least one of the plurality of coordinates. For example, the evaluating can be implemented in the following manner. Sub-step a) collecting raw data of a scalp characteristic by a detection device. Sub-step b) analyzing the raw data of the scalp characteristic to obtain a measured scalp characteristic for the scalp characteristic. In the sub-step b), an algorithm may be utilized to convert the raw data into the measured scalp characteristic. Alternatively, in the sub-step b), the measured scalp characteristic is included in the raw data and an algorithm to perform the convertion is not needed. In a possible embodiment, the scalp characteristic is pore size, the measured scalp characteristic is measured pore size, and the detection device is a non-invasive imaging device, such as a dermatoscope. The raw data is an image of a scalp captured by a built-in camera of the dermatorscope with a specialized magnifiying lens when the dermatoscope is pressed against the scalp. In sub-step b), the captured image is transferred to a computer or mobile device running specialized software. This software performs normalization and segmentation. For the normalization, the image is adjusted for lighting, contrast, and color to ensure consistent analysis. For the segmatation, the software, using machine learning or a deep learning model, identifies and separates different features in the image. The features can be pores, hair follicles, and surrounding skin. The model is trained on a vast dataset of skin images to recognize patterns associated with pores, hair follicles, and surrounding skin. It can distinguish a pore (an empty, dark depression) from a hair follicle (which may contain a hair shaft) and other features like spots or blemishes. Once the pores and follicles are segmented from the captured image, the software's algorithms measure their dimensions by means of calibration and measurement. For calibration, the software first calibrates the image by using a known reference scale (e.g., a ruler in the image or a pre-set magnification factor) to convert pixel measurements into real-world units (e.g., millimeters or micrometers). For measurement, the algorithm calculates the size of the identified pores. This can be the diameter, area, or other metrics, providing a quantitative measurement of the pore size. By means of the above, the measured pore size is obtained.

[0027] In a preferred embodiment, step b) involves evaluating at least one scalp characteristic at multiple predefined coordinates on the scalp surface. These coordinates may be part of a systematic grid or a specific mapping system that covers the entire surface area of the scalp. The evaluation process consists of analyzing scalp characteristics at each of these coordinates to gather precise data about the scalp condition. Scalp characteristics such as pore size, hydration level, skin color (including lightness, redness, and yellowness), hair follicle density, and sebum production, among others, are measured and documented. The outcome of this evaluation yields a detailed profile of the scalp's health and condition across different zones, providing crucial insights for both dermatological assessments and hair health analysis.

[0028] The scalp characteristics are defined as follows:

[0029] The term "pore size" refers to the visible openings of the hair follicles on the scalp surface. Larger pore sizes may be indicative of an oily or congested scalp, while smaller pore sizes can suggest a dry or well-balanced scalp condition. The term "hydration level" refers to the amount of moisture present in the scalp skin. A well-hydrated scalp is indicative of a balanced and healthy condition, whereas dehydration may result in dryness, irritation, or flaking of the scalp.

[0030] The term "skin color," as used herein, includes variations in lightness, redness, and yellowness of the scalp. Lightness may correspond to hypopigmentation or health, redness may indicate irritation or inflammation, and yellowness may be associated with oiliness or infection.

[0031] The term "hair follicle density" refers to the number of hair follicles present per square centimeter of the scalp surface. Higher follicle density typically corresponds to fuller hair coverage, while lower follicle density may suggest hair thinning or loss.

[0032] The term "hair thickness" refers to the diameter of individual hair strands on the scalp. Thicker hair may provide better coverage and protection to the scalp, whereas thinner hair can suggest fragility or genetic predispositions.

[0033] The term "scalp thickness" refers to the overall depth of the scalp tissue, including the skin, fat, and connective tissues. Greater scalp thickness may indicate enhanced protection, while reduced thickness can be associated with sensitivity or vulnerability.

[0034] The term "scalp pH" refers to the measure of the acidity or alkalinity of the scalp. A balanced scalp pH, typically ranging between 4.5 and 5.5, supports a healthy microbiome, while deviations from this range may lead to irritation, dandruff, or infection.

[0035] The term "microbiome composition" refers to the balance and diversity of microorganisms, including bacteria and fungi, that reside on the scalp. A healthy microbiome is indicative of a well-functioning scalp, while imbalances may contribute to dandruff or other scalp conditions.

[0036] The term "scalp temperature" refers to the measurement of heat on the scalp's surface. Elevated scalp temperature may indicate inflammation or increased metabolic activity, while lower temperature may suggest poor blood circulation. The term "pore characteristics" refers to various attributes of scalp pores, including their size, shape, and visibility. Changes in pore characteristics may reflect scalp conditions such as oiliness, congestion, or poor skin health.

[0037] The term "surface roughness" refers to the texture of the scalp surface. A smooth scalp surface is indicative of healthy skin, while roughness may suggest scaling, irritation, or dryness.

[0038] The term "skin conductance" refers to the ability of the upper layers of the scalp skin (stratum corneum) to conduct electricity, which is directly related to moisture content. Since water has a higher ability to conduct electricity than most materials, higher skin conductance values indicate increased hydration in the stratum corneum, while lower values suggest dryness or dehydration.

[0039] The term "skin capacitance" refers to the scalp's ability to store electrical charge, which is often linked to moisture content. Capacitance measurement is used to assess the dielectric constant of the upper layers of the skin (stratum corneum), as water has a higher dielectric constant than most materials. Higher capacitance values indicate a greater water content in the stratum corneum, reflecting a well-hydrated scalp, while lower values may suggest dehydration.

[0040] The term "water evaporation rate" refers to the rate at which moisture evaporates from the scalp surface. Increased water evaporation may indicate scalp dryness or compromised barrier function, while lower rates reflect a healthy scalp hydration level.

[0041] The term "electrical conductivity" refers to the overall ability of the upper layers of the scalp skin to conduct an electrical current, which is often influenced by the moisture content and electrolyte balance of the stratum corneum. Higher conductivity typically indicates better hydration and a healthy balance of electrolytes in these upper layers. The term "infrared radiation" refers to the emission of infrared energy from the scalp, typically associated with heat or metabolic activity. Higher infrared radiation may indicate increased blood flow or inflammation in the scalp. The term "lactic acid concentration" refers to the levels of lactic acid present in the scalp skin, a byproduct of cellular metabolism. Elevated lactic acid concentrations may be indicative of inflammation or pH imbalances.

[0042] The term "oleic acid concentration" refers to the levels of oleic acid present in the scalp skin, which is a byproduct of Malassezia yeast metabolism. Elevated oleic acid concentrations can lead to scalp irritation and inflammation, and in some cases, may contribute to hair follicle miniaturization. Excessive oleic acid is often associated with conditions such as dandruff or seborrheic dermatitis, as it disrupts the scalp’s natural barrier function and alters its pH balance.

[0043] The term "lipid peroxidation level" refers to the amount of oxidative damage affecting lipids within scalp cells. Higher levels of lipid peroxidation suggest oxidative stress, which may contribute to scalp aging or inflammation.

[0044] The term "skin oxidative stress level" refers to the balance between free radicals and antioxidants within the scalp. Elevated oxidative stress levels may result in scalp inflammation, damage, and premature aging.

[0045] The term "skin anti-oxidant potential" refers to the scalp's capacity to neutralize free radicals and reduce oxidative stress. Higher antioxidant potential indicates the scalp's ability to protect against oxidative damage.

[0046] The term "hair coverage condition" refers to the extent of hair present on the scalp. Fuller hair coverage is indicative of healthy scalp function, while reduced coverage may suggest hair loss or thinning.

[0047] The term "sebum production" refers to the amount of oil secreted by the sebaceous glands of the scalp. Normal sebum production supports scalp hydration, while excessive sebum can result in oiliness and inadequate production may lead to dryness.

[0048] The term "elasticity" refers to the ability of the scalp skin to stretch and return to its original form. A healthy scalp typically exhibits high elasticity, whereas reduced elasticity may indicate aging, dehydration, or skin damage. The term "sensitivity" refers to the responsiveness of the scalp to external stimuli, such as heat, chemicals, or pressure. Increased sensitivity may indicate scalp irritation or underlying conditions.

[0049] The term "moisture level" refers to the water content within the scalp skin. Higher moisture levels are indicative of a well-hydrated scalp, while lower levels may result in dryness, itching, or flaking.

[0050] The term "pigmentation" refers to the presence and distribution of melanin within the scalp skin. Variations in pigmentation may arise due to genetic factors, sun exposure, or conditions such as hyperpigmentation or vitiligo.

[0051] The term "scalp scaling" or "flaking" refers to the presence of visible flakes or scales on the scalp surface, often resulting from dryness, dandruff, or dermatological conditions like psoriasis.

[0052] The term "perifollicular scaling" refers to the accumulation of dead skin cells or scaling around individual hair follicles. This condition may indicate underlying skin disorders such as seborrheic dermatitis or psoriasis.

[0053] The term "porphyrin amount" refers to the concentration of porphyrins, which are byproducts of bacterial activity, present on the scalp surface. Elevated porphyrin levels may be indicative of bacterial imbalance or overgrowth, which can contribute to scalp conditions like acne or dandruff.

[0054] In a preferred embodiment, each coordinate is associated with a specific data point that relates to one or more scalp characteristics. These characteristics are systematically evaluated, either through physical measurement or advanced imaging technologies, to generate quantitative or qualitative metrics. This process enables accurate detection of variations in the scalp’s characteristics across different regions, allowing for targeted treatments and diagnostics. In a preferred embodiment, the measured scalp characteristics obtained in step b) are stored in a database for future reference and analysis. In this embodiment, the system captures and records the data for each evaluated coordinate in a centralized digital repository. The database can include various metrics such as skin moisture levels, hair follicle density, or the scalp’s microbiome composition, providing a comprehensive and accessible record of the scalp's condition. The database structure allows for longitudinal studies, comparative analysis over time, and the ability to track changes in the scalp's characteristics due to environmental factors, treatments, or health conditions. The stored data can be used for research, prediction of the future scalp state (without, and with suitable intervention using scalp care cosmetic products), personalized hair and scalp care, or diagnostics.

[0055] In a preferred embodiment, the collected data can also be utilized to predict future scalp conditions, including potential deficiencies and / or medical conditions. By continuously monitoring and analyzing scalp characteristics, such as hydration levels, sebum production, hair follicle density, and scalp temperature, this method allows for the detection of trends and patterns that may indicate the onset of scalp issues. Through the integration of advanced machine learning algorithms, the system can forecast future scalp health by identifying early warning signs, such as increased oxidative stress or changes in follicle activity. This predictive capability enables proactive scalp care, allowing for early intervention to prevent or mitigate the development of conditions like hair loss, seborrheic dermatitis, or scalp irritation.

[0056] In a preferred embodiment, the use of a database plays a critical role in the management, storage, and retrieval of scalp characteristic data obtained from non- invasive imaging techniques. A database serves as a centralized repository where information from multiple coordinates on the scalp can be stored, organized, and accessed efficiently. The data stored can include a wide array of scalp characteristics such as pore size, hydration level, skin color, hair follicle density, and more. The database is structured to handle large volumes of data and is designed to support the complex relationships between different scalp characteristics, allowing for multidimensional analysis and tracking of scalp health over time. In a preferred embodiment, the data obtained through various non-invasive imaging techniques, such as dermatoscopes, high-resolution photography, thermal cameras, ultrasound imaging devices, confocal microscopy, and spectrometers, is systematically stored in the database. Each piece of data is associated with specific coordinates on the scalp and linked to its corresponding scalp characteristic. For example, hydration levels from a spectrometer reading at a particular scalp coordinate are stored alongside pore size measurements from a dermatoscope at the same location. The storage process ensures that the data is organized in a structured format, such as rows and columns or within more advanced data structures like relational databases or cloudbased systems. Furthermore, the database allows for longitudinal tracking, meaning that multiple datasets can be stored for the same patient over time. This capability is essential for tracking changes in scalp conditions, enabling healthcare professionals to compare previous data with current readings to assess the effectiveness of treatments or identify potential scalp health issues.

[0057] In a preferred embodiment, the communication between the non-invasive imaging devices and the database is facilitated through secure data transmission protocols. The imaging devices, such as a thermal camera or spectrometer, are equipped with data connectivity features (e.g., Wi-Fi, Bluetooth, or wired connections), enabling realtime data transfer to the central database. These devices can either store the data locally and upload it to the database after the evaluation is complete, or they can transmit the data instantly during the imaging process. For instance, when a dermatoscope captures an image of the scalp at a particular coordinate, the image data is transmitted securely to the database via an encrypted communication protocol. The database then records the data, ensuring that it is accessible for future analysis. In modem systems, this data transfer can be facilitated by cloud-based platforms, enabling seamless and remote access to scalp characteristic data by authorized personnel, such as dermatologists or researchers.

[0058] In a preferred embodiment, the evaluation of the scalp characteristic in step b) is performed using non-invasive imaging techniques. These techniques allow for the detailed assessment of the scalp without causing discomfort or damage to the patient’s skin or hair. Non-invasive imaging tools enable the visualization of both superficial and subdermal features of the scalp, offering a high-resolution view of critical parameters such as hair follicle health, pore structure, and skin hydration. Non-invasive methods also enhance the accuracy of measurements by reducing potential interference from manual assessments or invasive procedures. By leveraging these technologies, a detailed scalp analysis can be conducted efficiently and safely, improving the accuracy of diagnostics and treatment plans. In a preferred embodiment, the at least one non- invasive imaging technique is selected from the group consisting of dermatoscope, high-resolution photography, thermal camera, ultrasound imaging device, confocal microscopy, and spectrometer.

[0059] A dermatoscope is a handheld magnifying device with a built-in light source that is used for the examination of the scalp. In relation to scalp evaluation, the dermatoscope allows for the enhanced visualization of surface features such as hair follicles, sebaceous glands, and blood vessels. This tool is particularly useful for diagnosing conditions such as alopecia, seborrheic dermatitis, and psoriasis. The magnification capability (typically between 10x and 20x) enables a detailed view of the follicular structure, scaling, and perifollicular erythema (redness around hair follicles). Additionally, it helps detect abnormalities in hair shafts, such as miniaturization or structural damage, which is essential for evaluating hair loss conditions like androgenetic alopecia. Dermatoscopes often incorporate polarized light to reduce glare and allow for better visualization of the deeper layers of the scalp. This feature helps clinicians assess pigmentation irregularities and vascular structures without the need for invasive techniques.

[0060] High-resolution photography is a non-invasive imaging technique that captures detailed images of the scalp at various coordinates. These images are taken with high- definition cameras, which provide excellent clarity and allow for the visualization of surface-level conditions such as flaking, dandruff, scalp lesions, and hair thinning. The key benefit of this technique in scalp evaluation is the ability to track changes over time, enabling comparative analysis of scalp and hair health. In addition, high- resolution photography helps document conditions like scaling, erythema (redness), and scalp pigmentation. It can be used for patient records, facilitating longitudinal studies of scalp health and hair growth. This technique is also commonly used in cosmetic and dermatological practices to monitor the effectiveness of hair treatments or to assess the progression of scalp disorders. A thermal camera captures the infrared radiation emitted by the scalp, allowing for the measurement of temperature variations across different regions. In the context of scalp evaluation, thermal imaging can be used to detect areas of abnormal heat distribution, which may indicate inflammation, poor blood circulation, or infection. For example, areas with increased temperature could signal localized inflammation, a common feature in scalp conditions such as folliculitis or seborrheic dermatitis. Thermal cameras are non-invasive and provide a visual representation of heat patterns on the scalp, making it possible to identify vascular issues or inflammatory hotspots. These images are often color-coded, with warmer areas appearing in red and cooler areas in blue, offering a quick and efficient means of assessing scalp health.

[0061] An ultrasound imaging device uses high-frequency sound waves to generate real-time images of the scalp’s deeper structures. In scalp evaluation, ultrasound provides detailed information about the thickness of the skin, the health of hair follicles, and the presence of subcutaneous fat and other tissue layers. It is particularly useful for assessing the depth and structure of the scalp, which is important in conditions like scarring alopecia, where the hair follicles may be destroyed or buried under fibrotic tissue. Ultrasound devices are also used to evaluate the blood flow within the scalp, providing insights into the vascular health of the region. This can help detect conditions like poor circulation, which may contribute to hair loss or delayed wound healing. The non-invasive nature of ultrasound makes it ideal for real-time, painless scalp evaluation.

[0062] Hyperspectral image capturing device captures light in many different wavelengths across a spectrum. This allows for analysis and distinction of oxygenated and deoxygenated haemoglobin via their different light absorption characteristics, to produce a spatial map of oxygen levels. Oxygen levels can show how well the scalp and hair follicles are supplemented by blood vasculature.

[0063] Confocal microscopy is a laser-based imaging technology that enables the detailed three-dimensional examination of scalp tissues at the cellular level. It provides high- resolution images of the epidermis, dermis, and hair follicles, allowing for a precise assessment of various scalp characteristics such as hydration, collagen density, and cellular health. In the context of scalp evaluation, confocal microscopy is used to analyze conditions like hair follicle miniaturization, inflammation, and scalp pigmentation disorders. This technique is highly valuable for identifying early signs of scalp disease that may not be visible on the surface. It can be used to assess the integrity of the skin barrier, measure the thickness of the scalp's layers, and observe the activity within sebaceous glands. Confocal microscopy is often used in research and clinical settings due to its ability to provide detailed, non-invasive visualization of scalp microstructures.

[0064] A spectrometer is an analytical tool used to measure the interaction of light with matter, specifically how much light is absorbed, emitted, or reflected by the scalp at different wavelengths. In scalp evaluation, spectrometry is used to assess the pigmentation, moisture content, and chemical composition of the scalp. For instance, it can provide insights into the levels of melanin, hemoglobin, and other chromophores in the scalp skin. Spectrometers are particularly useful for detecting oxidative stress, which may contribute to scalp aging and hair loss. They can also measure the scalp’s moisture levels, aiding in the diagnosis of conditions like dry scalp or seborrheic dermatitis. Spectrometry is a non-invasive technique and can be performed quickly, making it an efficient tool for both clinical diagnostics and research studies on scalp health.

[0065] In a preferred embodiment, pore size is evaluated by a non-invasive imaging technique selected from dermatoscope or confocal microscopy. A dermatoscope provides a magnified view of the scalp, allowing for a detailed examination of pore openings and their surrounding structures. Confocal microscopy, with its ability to create three- dimensional images, can offer a deeper understanding of the size and shape of pores at a cellular level, making it ideal for evaluating pore size with high precision.

[0066] In a preferred embodiment, hydration level is evaluated by a non-invasive imaging technique selected from spectrometer or confocal microscopy. A spectrometer can measure water content in the scalp skin by analyzing how different wavelengths of light interact with the skin. Confocal microscopy, through its detailed imaging of skin layers, allows the visualization of water retention within the scalp, providing a comprehensive assessment of hydration levels. In a preferred embodiment, skin color is evaluated by a non-invasive imaging technique selected from high-resolution photography or spectrometer. High-resolution photography captures detailed images of the scalp, enabling an accurate assessment of color variations such as redness, lightness, or yellowness. A spectrometer can quantify the intensity of specific color wavelengths, allowing for precise analysis of skin pigmentation and color imbalances.

[0067] In a preferred embodiment, hair follicle density is evaluated by a non-invasive imaging technique selected from dermatoscope, high-resolution photography, or ultrasound imaging device. A dermatoscope provides a clear view of individual follicles, while high- resolution photography captures the overall density of follicles across a specific area of the scalp. Ultrasound imaging can provide deeper insight into the follicle structure beneath the scalp surface.

[0068] In a preferred embodiment, hair thickness is evaluated by a non-invasive imaging technique selected from dermatoscope or confocal microscopy. A dermatoscope can magnify individual hairs for visual inspection of their thickness, while confocal microscopy can provide a cross-sectional view of hair shafts, giving precise measurements of hair diameter.

[0069] In a preferred embodiment, scalp thickness is evaluated by a non-invasive imaging technique selected from ultrasound imaging device. Ultrasound imaging allows for the measurement of the depth of the scalp layers, from the epidermis to the subcutaneous tissue, providing accurate data on scalp thickness.

[0070] In a preferred embodiment, scalp pH is evaluated by a non-invasive imaging technique selected from spectrometer. A spectrometer can analyze chemical composition and detect pH-related shifts in scalp tissues, enabling the precise measurement of the scalp’s acidity or alkalinity.

[0071] In a preferred embodiment, microbiome composition is evaluated by a non-invasive imaging technique selected from spectrometer or confocal microscopy. Spectrometry helps in detecting specific chemical markers indicative of microbial activity, while confocal microscopy can visualize microbial presence on the scalp at a cellular level. In a preferred embodiment, scalp temperature is evaluated by a non-invasive imaging technique selected from thermal camera. The thermal camera captures the heat emitted by the scalp, providing a color-coded representation of temperature variations, which can be useful for identifying inflammation or circulatory issues.

[0072] In a preferred embodiment, pore characteristics are evaluated by a non-invasive imaging technique selected from dermatoscope or confocal microscopy. These tools allow for in-depth observation of pore shape, size, and activity at various depths of the scalp.

[0073] In a preferred embodiment, surface roughness is evaluated by a non-invasive imaging technique selected from high-resolution photography or confocal microscopy. High- resolution photography captures visible surface irregularities, while confocal microscopy can provide a detailed view of the epidermal texture.

[0074] In a preferred embodiment, skin conductance is evaluated by a non-invasive imaging technique selected from spectrometer. Spectrometry measures the electrical properties of the scalp, providing insights into moisture levels and conductance.

[0075] In a preferred embodiment, skin capacitance is evaluated by a non-invasive imaging technique selected from spectrometer. This technique can assess the scalp's ability to store electrical charge, which is closely related to moisture content.

[0076] In a preferred embodiment, water evaporation rate is evaluated by a non-invasive imaging technique selected from spectrometer. By analyzing the scalp's moisture dynamics, a spectrometer can measure the rate at which water evaporates from the skin.

[0077] In a preferred embodiment, the water evaporation rate is evaluated by measuring transepidermal water loss (TEWL). TEWL is assessed using a series of small temperature and humidity sensors that measure at two distinct points above the skin surface. These sensors are positioned to detect changes in temperature and humidity, allowing for the determination of the flow rate of water vapor escaping from the scalp. By calculating the difference in water vapor levels between these two points, this method provides an accurate measure of scalp moisture loss, which is indicative of the skin’s barrier function and hydration levels.

[0078] In a preferred embodiment, electrical conductivity is evaluated by a non-invasive imaging technique, such as a spectrometer. This tool measures how well the upper layers of the scalp (stratum corneum) conduct electrical signals. Since the scalp's conductivity is influenced by its moisture content and ion levels, higher conductivity readings indicate increased hydration and moisture in the scalp, while lower readings suggest dryness or dehydration. Thus, evaluating the scalp's electrical conductivity helps in assessing its hydration and overall health.

[0079] In a preferred embodiment, infrared radiation is evaluated by a non-invasive imaging technique selected from thermal camera. A thermal camera detects the infrared energy emitted by the scalp, which is associated with its temperature and underlying metabolic processes.

[0080] In a preferred embodiment, lactic acid concentration is evaluated by a non-invasive imaging technique selected from spectrometer. Spectrometry, preferably FTIR spectroscopy, can measure the chemical composition of the scalp, including the presence of lactic acid as a byproduct of cellular activity.

[0081] In a preferred embodiment, oleic acid concentration is evaluated by a non-invasive imaging technique selected from spectrometer. Spectrometry, preferably FTIR spectroscopy, can measure the chemical composition of the scalp, including the presence of oleic acid as a byproduct of Malassezia metabolism.

[0082] In a preferred embodiment, lipid peroxidation level is evaluated by a non-invasive imaging technique, such as spectrometer or preferably IR spectroscopy. Spectrometry can detect oxidative stress markers, including the byproducts of lipid peroxidation. In this embodiment, no additional chemicals or labeling solutions are required, allowing for a label-free method of scanning the scalp using the device. This approach simplifies the process by eliminating the need for external fluorescent markers or UV detection, ensuring a more efficient and non-invasive assessment of lipid peroxidation. In a preferred embodiment, skin oxidative stress level is evaluated by a non-invasive imaging technique, such as spectrometer, ultra-weak photon emission, low-level chemiluminescence detection, or electrochemical detection (e.g., PAOT-skin). These tools help in identifying free radical damage and assessing the scalp’s overall oxidative stress status. The PAOT-skin method, based on PAOT Technology patented by the European Institute of Antioxidants (PCT / FR2019 / 052835), provides an advanced approach for measuring oxidative stress levels, enhancing the precision of scalp health diagnostics.

[0083] In a preferred embodiment, skin antioxidant potential is evaluated by a non-invasive imaging technique, such as spectrometer or electrochemical methods, including the PAOT score. The PAOT score, based on an electrochemical method, measures the scalp’s capacity to neutralize oxidative damage by detecting antioxidant levels. This technique offers a precise evaluation of antioxidant potential and can be used in conjunction with other methods to provide a comprehensive assessment of the scalp's ability to combat oxidative stress.

[0084] In a preferred embodiment, hair coverage condition is evaluated by a non-invasive imaging technique selected from high-resolution photography or dermatoscope. High- resolution images can capture the extent of hair coverage across the scalp, while a dermatoscope can provide magnified views for closer inspection.

[0085] In a preferred embodiment, sebum production is evaluated by a non-invasive imaging technique, such as dermatoscope, confocal microscopy, or spectrometry (including hyperspectral imaging). These techniques allow for the real-time visualization and quantification of sebum secretion at the scalp surface. Traditionally, sebum is measured using blotting paper and light transmission, but here, the measurement must be performed in real time. To achieve this, an algorithm must recognize the oily surface from the dermatoscope image, distinguishing between normal shine and excess oil. Machine learning techniques may be required to accurately differentiate between these conditions, making the process more efficient and precise.

[0086] In a preferred embodiment, elasticity is evaluated by a non-invasive imaging technique selected from confocal microscopy. This imaging technique allows for detailed visualization of the skin’s collagen and elastin networks, which are key to maintaining scalp elasticity.

[0087] In a preferred embodiment, sensitivity is evaluated by a non-invasive imaging technique selected from thermal camera. The thermal camera can help identify areas of the scalp that are more reactive to external stimuli, often indicated by localized temperature changes.

[0088] In a preferred embodiment, moisture level is evaluated by a non-invasive imaging technique, such as spectrometer, confocal microscopy, FTIR, NIR, or methods based on capacitance or conductance. These techniques are effective in measuring the water content within the scalp, providing accurate moisture level assessments by detecting variations in hydration levels across the scalp surface.

[0089] In a preferred embodiment, pigmentation is evaluated by a non-invasive imaging technique, such as spectrometer, high-resolution photography, or hyperspectral imaging. A spectrometer, including hyperspectral imaging, analyzes light absorption related to melanin, hemoglobin, and other skin components, while also detecting skin lesions and mapping oxygen levels. High-resolution photography documents visible pigmentation patterns, providing a comprehensive assessment of the scalp's pigmentation and related characteristics.

[0090] In a preferred embodiment, scalp scaling / flaking is evaluated by a non-invasive imaging technique, such as high-resolution photography, dermatoscope, or ultrasound. These techniques allow for detailed visualization of flaking, scaling, and other visible abnormalities on the scalp surface. Additionally, ultrasound can be used to assess epidermis and dermis thickness, providing further insight into the condition of the scalp tissues. Scalp elasticity and softness can also be measured through indentometry, offering a comprehensive analysis of scalp health.

[0091] In a preferred embodiment, scalp density is evaluated by a non-invasive imaging technique selected from ultrasound or optical coherence tomography. Ultrasound detects the echo of the sound waves that it emits into the scalp, measures the intensity and time to reach the receiver and forms a picture of the tissue, depending on the reflective ability of the tissue layers. Fluids are less reflective and appear darker, while solids are more reflective and appear whiter. Optical coherence tomography involves the measurement of the echo time delay and intensity of reflected light off skin tissue. It combines the reflected light with a reference light to form an interference pattern that determines the depth at which the light has penetrated and the layer of tissue it has reflected off.

[0092] In a preferred embodiment, scalp elasticity is evaluated by a non-invasive technique selected from cutometry or indentometry. Cutometry involves the measurement of elasticity by creating a vacuum on the skin thus deforming the skin by suction. The rate of deformation and restoration is measured by a light beam and detector. The analysis of the deformation curve gives the elastic, firmness, and viscoelastic properties of skin. Indentometry uses a probe with a tip to press into the skin at a fixed force. The depth of the indentation made indicates the firmness of the skin. The deeper the indentation made, the more elastic or less firm the skin is.

[0093] In a preferred embodiment, perifollicular scaling is evaluated by a non-invasive imaging technique selected from dermatoscope or confocal microscopy. These methods enable the precise examination of scaling around individual hair follicles, offering insights into underlying scalp conditions.

[0094] In a preferred embodiment, porphyrin amount is evaluated by a non-invasive imaging technique, such as spectrometer or confocal microscopy. Porphyrins, which are byproducts of bacterial metabolism, can be detected through light-based spectrometry, offering insight into the scalp’s microbiome and bacterial activity. Additionally, confocal microscopy can be used to study the fluorescence of different bacteria, as certain bacteria may fluoresce blue, green, red, or yellow, allowing for the detection and differentiation of various bacterial species, further enhancing the analysis of the scalp's microbiome.

[0095] In a preferred embodiment, bacterial presence is evaluated by a non-invasive imaging technique selected from spectrometer. Different microbes can produce certain chemicals such as porphyrins or pyoverdines that fluoresce when excited by different wavelengths of light. The emission spectra can be measured using light-based spectrometry, such as confocal microscopy, so as to determine and distinguish the presence and abundance of a particular class of microbes according to the emitted fluorescence. The abundance can be related to other measured parameters of scalp leading to further insights on condition and treatment.

[0096] In a preferred embodiment, the at least one scalp characteristic is evaluated over time to monitor changes. In a preferred embodiment, this method involves periodically assessing the scalp characteristics, such as hydration level, sebum production, or hair follicle density, at various coordinates on the scalp over a set duration. The goal is to observe and document how these characteristics evolve, allowing for the detection of any gradual improvements or deteriorations in scalp health. By monitoring scalp characteristics over time, healthcare providers can make informed decisions about treatment adjustments, early intervention in case of scalp health deterioration, or the confirmation of successful treatment outcomes. This method also provides valuable insights into how environmental factors, products, or lifestyle changes impact scalp health over time, offering a comprehensive view of the patient’s scalp condition trajectory.

[0097] In a preferred embodiment, this inventively claimed method allows for the continuous monitoring of the history of individual hair follicles over their lifetime. By tracking follicle activity at various stages, the system can provide valuable insights into the longevity and health of each follicle. This long-term tracking offers practitioners the ability to intervene early in cases of hair loss and provides a deeper understanding of the follicular lifecycle, ultimately leading to more effective and personalized scalp care treatments.

[0098] In a preferred embodiment, step c) involves the process of attributing the measured scalp characteristics, obtained from various non-invasive imaging techniques, to predefined coordinates on a scalp map. These coordinates form part of a systematic grid that covers the entire surface area of the scalp, enabling comprehensive evaluation and analysis of scalp conditions. Each measured scalp characteristic, whether it be pore size, hydration level, or hair follicle density, is linked to the specific coordinate from which the data was collected. This creates a spatially accurate representation of the scalp’s health and characteristics at each point of interest. This step allows for a detailed understanding of how different scalp characteristics vary across the scalp. For instance, regions near the vertex may show different levels of sebum production compared to the temporal areas, which may be more prone to thinning or scaling. By associating these data points with precise scalp coordinates, a clear and actionable scalp map is generated, offering healthcare professionals or researchers an easy-to-navigate visual representation of the entire scalp.

[0099] The scalp map is dynamic and interactive, allowing for the visual identification of patterns, trends, and irregularities. For example, if multiple points within a localized area exhibit high porphyrin amounts, this could indicate a potential bacterial imbalance or scalp disorder. The use of such a detailed scalp map is critical for personalized treatment planning and can support more targeted interventions.

[0100] In a preferred embodiment, in the process of attributing the measured scalp characteristics to the coordinates, each data point is annotated with its corresponding coordinate on the scalp map. In this embodiment, the method integrates each individual data point (such as a moisture reading or follicle density measurement) into the scalp map by associating it with a unique spatial identifier. The scalp map is thus annotated with detailed information at each coordinate, ensuring that the locationspecific data remains organized and easy to interpret. For instance, when a hydration level is measured at a particular coordinate on the scalp, that data point is marked or annotated on the map at the exact corresponding coordinate. This annotation process may include both quantitative data (such as hydration percentages or pH values) and qualitative information (such as the condition of the skin or follicles). Advanced mapping software or algorithms may automatically update the map in real-time, as new data points are added, providing an evolving and up-to-date visualization of the scalp.

[0101] This form of data integration is essential for creating a clear and comprehensive scalp health profile. It allows for the visualization of scalp characteristics in a way that highlights specific areas of concern. For example, regions with excessive dryness or redness can be easily identified and addressed. The annotation also facilitates comparison across different scalp zones (e.g., frontal, parietal, occipital), making it easier to assess asymmetries in scalp health or scalp conditions that may manifest differently in various areas. Furthermore, the annotated scalp map can be stored in the database for future reference, enabling historical comparisons to be made between past and present scalp evaluations. This is especially useful in treatment monitoring, where the effects of therapeutic interventions can be visually tracked over time by reviewing the changes in the scalp map’s annotated data points.

[0102] In a preferred embodiment, each data point corresponding to a measured scalp characteristic, such as pore size, hydration level, or sebum production, can be scored based on a predetermined scale. Fore example, a score is assigned to various scalp characteristics using a numerical scale, typically ranging from 1 (indicating the least seventy or minimal effect) to 5 (indicating the greatest seventy or effect). For instance, a characteristic like scalp redness could be scored with 1 representing no visible redness and 5 representing significant or permanent redness. Scoring each data point of a measured scalp characteristic provides a structured, quantitative approach to scalp evaluation that enhances the precision, consistency, and usefulness of scalp health assessments. This method not only supports better diagnostic and treatment planning but also enables advanced data processing and predictive capabilities, particularly when combined with database storage and analysis systems.

[0103] In a preferred embodiment, step d) involves generating a visual representation of the scalp by integrating the measured scalp characteristics with the predefined scalp coordinates. The visual image serves as a comprehensive tool, offering a detailed view of the scalp’s condition across different regions. This visual representation can include features such as pore size, hydration levels, sebum production, and other scalp characteristics. By mapping these attributes to specific coordinates, the visual image allows healthcare professionals, researchers, or cosmetic specialists to quickly assess the state of the scalp in a clear, interpretable format.

[0104] In a preferred embodiment, the visual image includes visual representation of at least two scalp characteristics. Thereby different kinds of scalp characteristics can be displayed on a same visual image. Preferably, different kinds of scalp characteristics can be displayed at the same time. For example, the visual image may include visual representation of surface roughness and sebum production. A plurality of factors, including the sebum production, can influence the surface roughness. For instance, the factors can include dandruff, sebum production, inflammatory conditions, hydration and barrier function, aging and environmental factors. The environmental factors include exposure to pollutants, harsh hair care products, and physical damage (e.g., from scratching or excessive brushing). By including surface roughness and sebum production into the visual image, the correlation between the two scalp characteristics can be reviewed and considered by practitioners. Thereby a more proper advice or recommendation can be provided. Moreover, the correlation can be easily demonstrated and explained to the patient.

[0105] In a possible implementation, the visual image including visual representation of two or more scalp characteristics can be realized by means of superimposition, which involves layering different visual elements on top of a base image. The superimposition is achieved using a combination of software and specific techniques. In one approach, layering and opacity can be adopted. Different scalp characteristics correspond to different layers. For instance, surface roughness and sebum production are treated as separate layers. By adjusting the opacity or transparency of each layer, how much the underlying image shows through can be controlled. This allows surface roughness and sebum production that occupy the same place (e.g. data points on the same coordinate) without completely obscuring each other, creating a blended or semitransparent effect. In another approach, masking can be adopted. A mask is an image that defines the transparency of another image. It's used to selectively show or hide parts of a layer. For example, a software could generate a mask that highlights data points of the surface roughness. This mask is then overlaid on the original image, making data points of sebum production stand out.

[0106] In a possible implementation, the visual image includes visual representation of scalp regions and at least one scalp characteristic. The scalp regions include frontal-parietal zone, temporal-lateral zones, upper occipital zone, middle occipital zone, lower occipital zone, crown and vertex. For instance, a line of contour for each scalp region can be included in the visual representation. Alternatively, a plurality of colours are allocated to the scalp regions respectively and each scalp region corresponds to a unique colour. The visual image can be implemented by a 3D image. The line of contour or the colours corresponding to the scalp regions can be displayed on the 3D image through a 3D model. Clinically, scalp characteristics can be associated with the scalp regions to a certain extent. For instance, sebum production tends to be higher on the frontal-parietal zone and the crown than that of other zones. By incorporating visual representation of scalp regions into the visual image, the correlation between a scalp characteristic and a specific scalp region among the scalp regions can be reviewed and considered by practitioners. Thereby a more proper advice or recommendation can be provided accordingly.

[0107] The image may be generated using advanced data visualization techniques, where each characteristic is represented in a manner that facilitates easy comparison across regions. For instance, characteristics like temperature or hydration levels could be color-coded to highlight variations across different scalp zones, enabling users to identify areas requiring attention or treatment. This dynamic visualization provides a practical tool for making informed decisions about scalp health interventions or tracking changes over time.

[0108] The term “heat map” refers to a visual representation where data values are displayed in color gradients, making it easier to identify patterns and differences in specific attributes across a given area. In the context of generating a visual image of the scalp based on measured characteristics, a heat map offers a simple and effective way to visualize variations in parameters such as scalp temperature, hydration levels, pore size, or sebum production across the scalp’s surface. In a preferred embodiment, heat maps are generated by assigning different colors or shades to represent the intensity or seventy of a particular scalp characteristic at each coordinate. For example: Highly hydrated areas of the scalp might be represented in blue, while drier areas may be depicted in yellow or red, providing an immediate visual cue for problematic regions. In a similar fashion, areas of increased scalp temperature (indicative of inflammation or poor blood flow) could be shown in warmer colors such as red, while cooler areas may appear in shades of blue.

[0109] Heat maps offer a clear and intuitive way of understanding the distribution of these characteristics across the scalp. The primary advantage of using heat maps is their ability to convey complex, multi-dimensional data in a two-dimensional, easily interpretable format. They are particularly effective for large-scale comparisons, where numerous characteristics are measured across many coordinates.

[0110] The term “Augmented reality (AR) overlays” refers to a cutting-edge approach for visualizing scalp characteristics in real-time, offering an interactive and dynamic method for displaying data directly on the user’s field of view. In this embodiment, AR overlays allow the measured scalp characteristics, such as hair follicle density, scalp scaling, or pore characteristics, to be superimposed onto a live or virtual image of the scalp. These overlays provide practitioners with an enhanced view of scalp conditions during examinations or treatments. For example, during a real-time scalp assessment, AR overlays could visually represent: Hydration levels or redness directly on the patient’s scalp image. Hair density and follicle health overlaid on a video feed, helping practitioners visualize where thinning or miniaturization is occurring. This technique is particularly useful for precision diagnostics and treatment planning because it enables real-time interactivity. Practitioners can adjust their treatment approach based on the live feedback from the AR overlays. Additionally, AR overlays help in explaining conditions to patients, as the visual representation can be displayed directly on their scalp or in a virtual model, enhancing their understanding of the scalp’s health and proposed treatments.

[0111] In relation to generating a visual image of the scalp based on measured characteristics and coordinates, the term “3D models” refers to a detailed, three-dimensional representation of the scalp that allows for interactive exploration. Unlike 2D images or heat maps, a 3D model provides a more comprehensive view by incorporating the natural contours and curvatures of the scalp, which is essential for an accurate understanding of complex characteristics like scalp thickness, hair follicle density, and surface roughness.

[0112] In this preferred embodiment, the data from the measured characteristics is mapped onto a 3D scalp model, which users can rotate, zoom into, and explore from multiple angles. Each scalp characteristic, such as pore size, sebum production, or scalp scaling, is visually represented on this 3D model. Users can click on specific coordinates or regions of the scalp to access detailed data points for that area. The 3D model approach has several technical advantages: It allows for a precise visualization of how characteristics such as hair density or moisture content vary across different scalp zones, including hard-to-see areas like the crown or behind the ears. Practitioners can manipulate the 3D model to view the scalp from various perspectives, which is especially useful for conditions that affect the scalp’s shape, such as scarring alopecia or severe scaling. 3D models can store data from multiple sessions, allowing users to compare the scalp’s condition over time, visually documenting improvements or deteriorations in response to treatment.

[0113] In a preferred embodiment, the visual image of the scalp that is generated in step d) including a visual representation of a scalp health index. Each coordinate on the scalp corresponds to a scalp heath index that is based on at least one scalp characteristic on that coordinate. In a possible implementation, the scalp heath index is a function of the at least one scalp characteristic and a scalp region where the at least one scalp characteristic is located. In other words, the scalp health index is determined by taking at least two factors into consideration. The at least two factors include the at least on scalp characteristic and the scalp region. In a possible implementation, the scalp health index is a function of scalp scaling and a scalp region. Specifically, the value of the scalp health index equals to the value of the scalp scaling multiplied by a weight for the scalpe region. From a clinical point of view, different scalp zones tend to have different scaling severities. For example, the scaling severity on parietal zone and crown tends to be higher. The scaling seventy on middle occipital zone and lower occipital zone tends to be lower. The value of the weight for the parietal zone is less than the value of the weight for the lower occipital zone. Thereby the influence of different scalp regions on the scalp scaling is compensated and values of the scalp health index on one scalp region is comparable with values of the scalp health index on another scalp region.

[0114] In a preferred embodiment, the visual image of the scalp including the visual representation of the scalp health index is displayed using a 3D model. Specifically, values of the scalp heath index are mapped onto the 3D model wherein each coordinate of the scalp on the 3D model is assigned a corresponding value of the scalp health index. In a possible implementation, “heat map” can be utilized to provide a visual representation of the values of the scalp health index. For a possible implementation of the “heat map”, reference can be made to other paragraphs of the description.

[0115] Displaying the visual image of the scalp including the visual representation of the scalp health index using a 3D model wherein a heat map is utilized to provide the visual represention of values of the scalp health index, a clear and intuitive way of understanding the comprehensive health of the scalp is provided. Moreover, as the values of the scalp health index are based on corresponding scalp regions, balanced and comparable values of the scalp health index among different scalp regions can be obtained. A more accurate diagnosis and a more appropriate recommendation can be made based on the visual image of the scalp including the visual representation of the scalp health index.

[0116] In a preferred embodiment, step e) involves diagnosing the health and condition of the scalp by analyzing the visual images generated from the previous steps and the measured scalp characteristics obtained at specific coordinates. This step integrates both qualitative and quantitative data, such as pore size, hydration levels, or hair follicle density, across various scalp regions to identify any deficiencies or medical conditions. By examining these attributes, healthcare professionals can determine the overall scalp health and pinpoint any abnormalities, such as seborrheic dermatitis, psoriasis, or androgenetic alopecia. The visual representation, which may include heat maps, augmented reality overlays, or 3D models, enhances the diagnostic process by providing an intuitive view of the variations in scalp characteristics across different coordinates.

[0117] In a preferred embodiment, the analysis in step e) can be enhanced using machine learning (ML) and artificial intelligence (Al) models. These models are trained to recognize patterns in the scalp data by comparing the visual images and measured scalp characteristics against a database of known conditions. By applying advanced algorithms, Al can predict potential scalp issues, such as early signs of hair thinning or abnormal sebum production. These technologies allow for automated diagnosis, reducing the need for manual interpretation and increasing the accuracy and speed of scalp assessments. Al models may also incorporate historical data from past scalp evaluations, allowing them to learn and improve over time. For example, Al could detect patterns of hair loss progression in a patient by comparing the data collected over multiple sessions. Machine learning algorithms are particularly effective at identifying subtle trends that may not be easily visible to the human eye, such as early-stage follicular miniaturization, which may indicate future hair loss.

[0118] In a preferred embodiment, the diagnosis of the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics leads to the identification of a deficiency and / or medical condition selected from the group consisting of scalp psoriasis, scalp acne, folliculitis, scalp eczema, seborrheic dermatitis, hair loss, hair thinning, abnormal follicle health, alopecia areata, tinea capitis, traction alopecia, and scalp infection.

[0119] In a preferred embodiment, scalp psoriasis is a chronic autoimmune condition that results in the rapid buildup of skin cells, leading to scaling, inflammation, and redness. It is commonly associated with scalp scaling / flaking, perifollicular scaling, and redness. Pore characteristics might also be affected as the buildup of skin cells blocks pores, leading to thick plaques. Additionally, skin oxidative stress levels and lipid peroxidation levels are elevated due to the chronic inflammation. Scalp pH can also be disrupted, contributing to irritation. Hydration level is often reduced, contributing to the skin’s dryness and scaling.

[0120] In a preferred embodiment, scalp acne occurs when hair follicles on the scalp become clogged with oil, dead skin cells, or bacteria, leading to inflammation and pimples. It is closely related to increased pore size and sebum production, which can lead to congestion of pores. Microbiome composition plays a role, as bacterial imbalances may worsen acne. Skin color, particularly redness, is often observed in inflamed areas, and pore characteristics are altered as the clogged pores lead to follicular irritation. Scalp temperature may also increase due to localized inflammation.

[0121] In a preferred embodiment, folliculitis is an infection or inflammation of the hair follicles, often caused by bacteria or fungi. It is characterized by perifollicular scaling, redness, and localized pus-filled bumps. Pore size is often increased in affected areas, while microbiome composition changes due to the presence of pathogenic organisms. Skin oxidative stress levels and scalp temperature are elevated due to the inflammation. Hair follicle density can be impacted as prolonged folliculitis may lead to hair thinning or scarring.

[0122] In a preferred embodiment, scalp eczema, also known as atopic dermatitis, is a condition that causes itchy, inflamed, and dry patches on the scalp. It is associated with reduced hydration level and increased scalp scaling / flaking. Scalp redness and surface roughness are often observed, and skin capacitance is lowered due to moisture loss. Sebum production may also be affected, either reduced in dry areas or increased in oily patches, exacerbating irritation. Skin elasticity is reduced in affected areas, leading to cracking or splitting.

[0123] In a preferred embodiment, seborrheic dermatitis is a chronic inflammatory condition characterized by flaking and greasy patches on the scalp. It is related to excessive sebum production, resulting in oily, scaly areas with yellowish flakes. Pore characteristics may be affected as sebum overproduction leads to congested follicles. Hydration levels are often uneven, with greasy patches being overly hydrated while other areas are dry and flaky. Scalp scaling / flaking, surface roughness, and microbiome composition are also critical factors in the development of seborrheic dermatitis.

[0124] In a preferred embodiment, hair loss, or alopecia, occurs for various reasons, including genetic factors, hormonal changes, or medical conditions. It is characterized by a decrease in hair follicle density, hair thickness, and hair coverage condition. Pore characteristics may show thinning follicles, while scalp pH imbalances and oxidative stress levels are often elevated in conditions leading to hair loss. Microbiome composition and scalp temperature can also play a role, particularly in conditions like alopecia areata.

[0125] In a preferred embodiment, hair thinning is a progressive reduction in the diameter of hair strands, often related to hormonal changes, aging, or nutritional deficiencies. Hair thickness and hair follicle density are the primary characteristics affected. Scalp temperature may fluctuate depending on blood flow and circulation, while oxidative stress levels and scalp hydration levels can contribute to the condition. Pore characteristics may show miniaturized follicles as hair thinning.

[0126] In a preferred embodiment, abnormal follicle health refers to damaged or poorly functioning hair follicles, which can lead to hair loss or thinning. It is often associated with alterations in pore characteristics, hair follicle density, and hair thickness. Scalp oxidative stress levels, lactic acid concentration, and lipid peroxidation are often elevated in cases of follicular damage. Skin elasticity and hydration level can also affect follicle health.

[0127] In a preferred embodiment, alopecia areata is an autoimmune disorder that causes patchy hair loss on the scalp and other areas of the body. It is characterized by reduced hair follicle density and hair coverage condition in specific regions. Pore characteristics may show sudden follicle inactivity, and scalp temperature in affected areas might drop due to reduced metabolic activity. Microbiome composition could also be altered, contributing to inflammatory processes.

[0128] In a preferred embodiment, tinea capitis, or scalp ringworm, is a fungal infection that causes patchy hair loss, scaling, and itching. It is closely linked to scalp seal ing / flaking, surface roughness, and altered microbiome composition due to fungal overgrowth. Pore size and pore characteristics may be affected as the infection disrupts the follicle environment. Skin color, particularly redness and yellowness, may be present around infected areas, and scalp pH can shift due to the fungal presence.

[0129] In a preferred embodiment, traction alopecia is caused by continuous pulling or tension on the hair, leading to gradual hair loss. It is associated with reduced hair follicle density and hair thickness in areas subjected to tension. Pore characteristics may reveal stressed or damaged follicles, and skin elasticity in affected regions can decrease due to prolonged pulling. Scalp thickness may be reduced in regions where the hair has been consistently pulled.

[0130] In a preferred embodiment, a scalp infection, caused by bacteria, viruses, or fungi, results in inflamed, irritated, and often painful regions on the scalp. Pore size, pore characteristics, and microbiome composition are heavily impacted by the presence of pathogenic organisms. Skin color, particularly redness, and scalp temperature are elevated due to inflammation. Scalp pH may also become imbalanced, facilitating microbial overgrowth. Hydration level and sebum production may fluctuate depending on the nature of the infection.

[0131] In a preferred embodiment, the inventively claimed method also involves the combination of using several different non-invasive imaging techniques to evaluate various scalp characteristics simultaneously. By leveraging devices such as dermatoscopes, high-resolution photography, thermal cameras, ultrasound imaging, confocal microscopy, and spectrometers, the method enables a comprehensive analysis of multiple scalp characteristics. These characteristics include pore size, hydration level, sebum production, hair follicle density, scalp temperature, and more.

[0132] The combination of multiple imaging techniques enhances the diagnostic process by providing multi-dimensional insights into the scalp's health. For instance, while a thermal camera can detect abnormalities in scalp temperature, which might indicate inflammation, a dermatoscope can simultaneously evaluate hair follicle density and pore characteristics for signs of conditions like folliculitis or alopecia. Confocal microscopy provides in-depth analysis at the cellular level, offering detailed views of the skin's layers, while spectrometry can assess biochemical markers, such as oxidative stress or pigmentation levels. By integrating data from multiple imaging modalities, the method provides a higher level of diagnostic accuracy compared to using a single technique. Each device captures unique aspects of the scalp, and when combined, these insights offer a more complete and nuanced understanding of the scalp’s condition. This multi-technique approach minimizes the chances of misdiagnosis, allowing for early identification of scalp deficiencies and medical conditions, such as seborrheic dermatitis, scalp psoriasis, or alopecia, before they become clinically apparent. The result is a more robust and reliable diagnostic process, improving patient outcomes and enabling more targeted treatment interventions.

[0133] In a preferred embodiment, this diagnostic method can detect early warning signs of scalp deficiencies or medical conditions before they become clinically noticeable. For example, Al models can flag early signs of scalp inflammation, oxidative stress, or follicular degradation that may not yet be visible through physical examination. These early-stage indicators allow healthcare professionals to intervene sooner with treatments designed to prevent the progression of the condition, such as moisturizing the scalp to prevent severe dryness or applying anti-inflammatory treatments. By identifying potential issues before they become symptomatic, this method can help in proactive management of scalp health, reducing the likelihood of more serious conditions developing over time. For instance, excessive sebum production combined with early signs of scalp redness might indicate a predisposition to seborrheic dermatitis, which can be addressed early with appropriate shampoos or topical treatments.

[0134] In a preferred embodiment, the analysis can include cross-referencing the measured scalp characteristics with a database of known scalp conditions. This database would contain detailed profiles of various scalp disorders, including characteristic data such as pore size, scalp pH, sebum production, and scalp temperature. By comparing the measured data from the patient’s scalp with this reference database, the system can provide a more accurate diagnosis. For example, the system might detect a pattern of increased redness and flakiness that matches the profile of psoriasis, prompting a recommendation for further investigation or treatment. This cross-referencing allows for data-driven diagnosis, where each scalp characteristic is matched against the database to find the closest condition profile. The process leverages Al and machine learning to provide clinicians with diagnostic suggestions, making the process faster and more reliable. Additionally, cross-referencing helps in reducing human error, ensuring that even rare or less obvious conditions are considered during the diagnostic process.

[0135] In a preferred embodiment, in step f), the process involves displaying the analyzed scalp data in an accessible and understandable format for both healthcare professionals and patients. The system integrates the visual representation of scalp characteristics, such as pore size, hydration levels, scalp temperature, and other metrics collected in previous steps, into user-friendly interfaces like scalp maps, heat maps, or 3D models. These visual formats provide a comprehensive view of the scalp’s condition across different zones and coordinates, allowing for immediate identification of problem areas or regions that may require closer attention. The visual display may be enhanced with interactive features, where users can click on specific scalp regions to obtain detailed information about measured characteristics at that coordinate. For instance, a healthcare professional might be able to view data on hydration levels, sebaceous gland activity, or hair follicle density by selecting different parts of the scalp on the map. This visual data helps practitioners communicate the scalp’s state more effectively to the patient, ensuring clarity in diagnosis and treatment plans.

[0136] In this preferred embodiment, the system provides personalized recommendations based on the analysis of the scalp data. These recommendations may include suggestions for specific treatments, such as topical scalp products, hydration therapies, or anti-inflammatory medications. The system may also recommend procedural interventions, such as laser therapy, depending on the identified scalp condition. For example, in cases where the system detects abnormal sebum production or scalp scaling, it may recommend specific shampoos or lotions designed to reduce oil or scaling. The recommendations generated are cross-referenced with a database of known scalp conditions and treatments. This ensures that the suggested interventions are based on established medical knowledge and proven treatment efficacy. The system uses the database to match the identified scalp condition — such as psoriasis, folliculitis, or seborrheic dermatitis — with the most appropriate treatments or therapies. This helps practitioners make evidence-based decisions, improving the likelihood of successful treatment outcomes.

[0137] In a further embodiment, the database may also provide alternative recommendations for cases where initial treatments prove ineffective, thus ensuring a comprehensive approach to scalp care. The system could adjust recommendations over time based on the progression of scalp health, using past data to refine future suggestions.

[0138] Another key feature of this embodiment is the ability to display scalp health data in real-time. As the system continuously collects new data from imaging techniques like thermal cameras or dermatoscopes, the visual representation of the scalp is updated accordingly. This enables ongoing monitoring of scalp health and allows healthcare professionals to track how the condition changes during treatment or over time. Realtime updates allow practitioners to adjust treatment plans dynamically based on the most current information, optimizing patient care. For instance, if a patient is undergoing a treatment for alopecia areata, the practitioner can monitor changes in hair follicle density or scalp redness in real-time, making adjustments to the treatment plan as needed. This method of real-time monitoring and visual display of scalp characteristics provides a detailed, data-driven approach to scalp health management.

[0139] The presently claimed invention also relates to a system comprising several key components for the evaluation, analysis, and display of scalp characteristics. This system integrates advanced technologies to provide a comprehensive and accurate assessment of the scalp’s health across various coordinates. The system includes at least one device for evaluating at least one scalp characteristic using non-invasive imaging techniques. These devices may include dermatoscopes, high-resolution cameras, thermal cameras, ultrasound imaging devices, confocal microscopy, or spectrometers. The purpose of these devices is to collect detailed data on scalp characteristics such as hydration levels, pore size, sebum production, and hair follicle density at multiple coordinates on the scalp. In a preferred embodiment, the system is configured to perform the method for diagnosing the state of the scalp. Specifically, the system is configured to perform the method steps a) to e). Preferably, the system is configured to perform the step f). More preferably, the system is configured to implement the embodiments of the method described above. In a possible embodiment, the system may include technical means describle above, so as to implement the method steps as well as the embodiments of the method. For example, the system includes the grid system mentioned above. And the grid system is to perform the step a). The system may further include the non-invasive imaging device, such as the dermatoscope, as well as the the computer or the mobile device running the specialized software. The non-invasive imaging device as well as the computer or the mobile device running the specialized software are to perform the step b). The step c) can be performed by means of the grid system, the non-invasive imaging device as well as the computer or the mobile device running the specialized software. The system may further include hardware and software that implement the functions of heat maps, augmented reality overlays or 3D models. The system can perform the step d) by means of the hardware and software. The system may further include machine learning algorithms and artificial intelligence models. The system can perform the step e) by means of the machine learning algorithms and the artificial intelligence models. The system may further include the imaging unit capable of generating a visual image of the scalp based on the measured characteristics and the scalp map coordinates. For instance, the image unit can be devices such as Canfield Scientific's systems (e.g., VECTRA), FotoFinder Systems or Specialized 3D hair and scalp analyzers. The system can perform the step f) by means of the imaging unit.

[0140] The system further comprises at least one computer for attributing the measured scalp characteristics to the corresponding coordinates on a scalp map. The computer processes the data collected by the non-invasive imaging devices and links each characteristic to its respective coordinate, ensuring a precise, spatially accurate map of the scalp. This computerized process enables efficient and accurate organization of the scalp data, making it accessible for further analysis and visualization.

[0141] In addition, the system includes at least one database for storing the information related to the scalp characteristics and the plurality of coordinates. The database serves as a centralized repository where all measured data is securely stored and can be referenced during diagnostics or treatment. The database can also store historical data, enabling practitioners to track changes in scalp health over time. The stored data can be cross-referenced with known scalp conditions, allowing for pattern recognition and more informed decision-making.

[0142] By utilizing the large data collected, a predictive model better tailored to the individual can be developed. Typical large data models use one set of measurements taken from individual subjects in a broad-based population to create or train the model. By tracking multiple individuals over a determined period, the model can be better equipped to predict scalp changes in a more personalized manner.

[0143] Moreover, the system comprises at least one imaging unit capable of generating a visual image of the scalp based on the measured characteristics and the scalp map coordinates. This unit can create detailed visual representations, such as heat maps, 3D models, or augmented reality overlays, providing a comprehensive view of the scalp's condition. The imaging unit offers an intuitive interface for users, allowing healthcare professionals to interact with the visual data and identify areas that require attention. The presently claimed invention also is a computer-implemented method. This method involves the automation of key steps, including the input of data from non-invasive imaging devices, the attribution of measured scalp characteristics to coordinates, and the storage and retrieval of data from the database. The method ensures that the system can analyze and process large datasets efficiently, providing accurate scalp diagnostics and treatment recommendations based on objective, measurable characteristics. By implementing this method through computing systems, the invention improves both the speed and accuracy of scalp assessments, contributing to enhanced patient care and scalp health management.

[0144] A system is further disclosed. The system comprises a processor and a memory that is coupled to the processor. The memory stores instructions which, when the instructions are executed by the processor, cause the system to perform the method for diagnosing the state of the scalp. Specifically, the instructions cause the system to perform the method steps a) to e). Preferably, the instructions cause the system to perform the step f). More preferably, the instructions cause the system to implement the embodiments of the method described above.

[0145] A computer program product is further disclosed. The computer program product comprises instructions which, when the instructions are executed on a computer, cause the computer to perform the method for diagnosing the state of the scalp. Specifically, the instructions cause the computer to perform the method steps a) to e). Preferably, the instructions cause the computer to perform the step f). More preferably, the instructions cause the computer to implement the embodiments of the method described above.

[0146] The presently claimed invention is associated with at least one of the following technical benefits.

[0147] • The presently claimed invention uses non-invasive imaging techniques for a comprehensive and accurate evaluation of scalp characteristics without causing discomfort or damage to the patient’s scalp. • The use of systematic mapping and dynamic coordinate grids ensures that all areas of the scalp are thoroughly assessed, facilitating detailed and consistent evaluations across different regions.

[0148] • The database-driven approach allows for the longitudinal tracking of scalp health, enabling practitioners to monitor changes over time and make data- driven treatment recommendations.

[0149] • The ability to generate visual representations such as heat maps, 3D models, and augmented reality overlays allows for intuitive and interactive scalp evaluations, offering healthcare professionals and patients clear, interpretable insights into scalp health.

[0150] • The presently claimed invention provides a high level of detail, down to the individual hair follicle. This allows for the precise monitoring of changes in hair follicle size, density, activity, and overall health, giving practitioners the ability to detect early signs of conditions such as follicular miniaturization.

[0151] According to the present invention, further implementations are disclosed:

[0152] In a first aspect, a system for diagnosing the state of the scalp is provided. The system is configured to: divide a scalp into a plurality of coordinates to create a scalp map, wherein each coordinate corresponds to the surface of the scalp; evaluate at least one of the plurality of coordinates for at least one scalp characteristic in each coordinate to obtain a measured scalp characteristic; attribute the measured scalp characteristics to the plurality of coordinates on the scalp map; generate a visual image of the scalp based on the measured scalp characteristics and the plurality of coordinates, providing a comprehensive view of the scalp’s characteristics across different coordinates; diagnose the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics, and identify a deficiency and / or medical condition. In a first implementation, according to the first aspect, the system is further configured to: display the state of the scalp in an accessible format, and provide recommendations.

[0153] In a second implementation, according to the first aspect or the first implementation, the plurality of coordinates is located in each of the scalp regions selected from the group consisting of frontal-parietal zone, temporal-lateral zones, upper occipital zone, middle occipital zone, lower occipital zone, crown and vertex.

[0154] In a third implementation, according to the first aspect or any one of the preceding implementations thereof, the plurality of coordinates is determined by a grid system which is tailored to an individual’s scalp dimensions and contours.

[0155] In a fourth implementation, according to the first aspect or any one of the preceding implementations thereof, the at least one scalp characteristic is selected from the group consisting of pore size, hydration level, skin color color including lightness, redness and yellowness, hair follicle density, hair thickness, scalp thickness, scalp pH, microbiome composition, scalp temperature, pore characteristics, surface roughness, skin conductance, skin capacitance, water evaporation rate, electrical conductivity, infrared radiation, lactic acid concentration, oleic acid concentration, lipid peroxidation level, skin oxidative stress level, skin anti-oxidant potential, hair coverage condition, sebum production, elasticity, sensitivity, moisture level, pigmentation, scalp scaling I flaking, perifollicular scaling, and porphyrin amount.

[0156] In a fifth implementation, according to the first aspect or any one of the preceding implementations thereof, the scalp characteristics are stored in a database.

[0157] In a sixth implementation, according to the first aspect or any one of the preceding implementations thereof, the at least one scalp characteristic is evaluated by at least one non-invasive imaging technique.

[0158] In a seventh implementation, according to the sixth implementation, the at least one non-invasive imaging technique is selected from the group consisting of dermatoscope, high-resolution photography, thermal camera, ultrasound imaging device, confocal microscopy, and spectrometer.

[0159] In an eighth implementation, according to the first aspect or any one of the preceding implementations thereof, the at least one scalp characteristic is evaluated over time to monitor changes.

[0160] In a ninth implementation, according to any one of the first implementation to the eighth implementation, the visual image is displayed using a technique selected from the group consisting of heat maps, augmented reality overlays and 3D models.

[0161] In a tenth implementation, according to the first aspect or any one of the preceding implementations thereof, the visual image includes visual representation of at least two scalp characteristics.

[0162] In an eleventh implementation, according to the first aspect or any one of the preceding implementations thereof, the visual image includes visual representation of scalp regions and at least one scalp characteristic.

[0163] In a twelfth implementation, according to the first aspect or any one of the preceding implementations thereof, the visual image includes a visual representation of a scalp health index. The scalp heath index is based on at least one scalp characteristic and a scalp region where the at least one scalp characteristic is located.

[0164] In a thirteenth implementation, according to the first aspect or any one of the preceding implementations thereof, the analysis of the visual image and measured scalp characteristics is performed by using machine learning algorithms and artificial intelligence models.

[0165] In a fourteenth implementation, according to the first aspect or any one of the preceding implementations thereof, the deficiency and / or medical condition is selected from the group consisting of scalp psoriasis, scalp acne, folliculitis, scalp eczema, seborrheic dermatitis, hair loss, hair thinning, abnormal follicle health, alopecia areata, tinea capitis, traction alopecia, and scalp infections. In a fifteenth implementation, according to the first aspect or any one of the preceding implementations thereof, the system is configured to: identify early warning signs of potential scalp medical conditions and deficiencies before they become clinically apparent.

[0166] In a sixteenth implementation, according to the first aspect or any one of the preceding implementations thereof, the system is configured to: cross-reference the measured scalp characteristics with a database of known scalp medical conditions and their characteristics.

[0167] In a seventeenth implementation, according to the first aspect or any one of the preceding implementations thereof, the system comprises a processor and a memory that is coupled to the processor. The memory stores instructions which, when the instructions are executed by the processor, cause the system to perform the following steps: divide a scalp into a plurality of coordinates to create a scalp map, wherein each coordinate corresponds to the surface of the scalp; evaluate at least one of the plurality of coordinates for at least one scalp characteristic in each coordinate to obtain a measured scalp characteristic; attribute the measured scalp characteristics to the plurality of coordinates on the scalp map; generate a visual image of the scalp based on the measured scalp characteristics and the plurality of coordinates, providing a comprehensive view of the scalp’s characteristics across different coordinates; diagnose the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics, and identify a deficiency and / or medical condition;

[0168] In an eighteenth implementation, according to the seventeenth implementation, when the instructions are executed by the processor, the system is caused to perform: display the state of the scalp in an accessible format, and provide recommendations. In a second aspect, a computer program product is provided. The computer program product comprises instructions which, when the instructions are executed on a computer, cause the computer to perform the following steps: divide a scalp into a plurality of coordinates to create a scalp map, wherein each coordinate corresponds to the surface of the scalp; evaluate at least one of the plurality of coordinates for at least one scalp characteristic in each coordinate to obtain a measured scalp characteristic; attribute the measured scalp characteristics to the plurality of coordinates on the scalp map; generate a visual image of the scalp based on the measured scalp characteristics and the plurality of coordinates, providing a comprehensive view of the scalp’s characteristics across different coordinates; diagnose the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics, and identify a deficiency and / or medical condition;

[0169] In a nineteenth implementation, according to the second aspect, the first aspect or any one of the preceding implementations thereof, when the instructions are executed on the computer, the computer is caused to perform: display the state of the scalp in an accessible format, and provide recommendations.

[0170] In a third aspect, a system for diagnosing the state of the scalp is provided. The system comprises at least one device, at least one computer, at least one database and at least one imaging unit. The at least one device is for evaluating at least one scalp characteristic using non-invasive imaging techniques. The at least one computer is for attributing the measured scalp characteristics to the corresponding coordinates. The at least one database is for storing the information related to the scalp characteristics and the plurality of coordinates. The at least one imaging unit is capable of generating a visual image of the scalp based on the measured characteristics and the scalp map coordinates.

Claims

Claims:1 . A method for diagnosing the state of the scalp comprising at least the steps of: a) dividing a scalp into a plurality of coordinates to create a scalp map, wherein each coordinate corresponds to the surface of the scalp; b) evaluating at least one of the plurality of coordinates for at least one scalp characteristic in each coordinate to obtain a measured scalp characteristic; c) attributing the measured scalp characteristics to the plurality of coordinates on the scalp map; d) generating a visual image of the scalp based on the measured scalp characteristics and the plurality of coordinates, providing a comprehensive view of the scalp’s characteristics across different coordinates; e) diagnosing the state of the plurality of coordinates of the scalp by analyzing the visual image and the measured scalp characteristics, and identifying a deficiency and / or medical condition; optionally f) displaying the state of the scalp in an accessible format, and providing recommendations.

2. The method according to claim 1 , wherein the plurality of coordinates is located in each of the scalp regions selected from the group consisting of frontal-parietal zone, temporal-lateral zones, upper occipital zone, middle occipital zone, lower occipital zone, crown and vertex.

3. The method according to claim 1 or 2, wherein the plurality of coordinates is determined by a grid system which is tailored to an individual’s scalp dimensions and contours.

4. The method according to any one of claims 1 to 3, wherein the at least one scalp characteristic is selected from the group consisting of pore size, hydration level, skin color color including lightness, redness and yellowness, hair follicle density, hair thickness, scalp thickness, scalp pH, microbiome composition, scalp temperature, pore characteristics, surface roughness, skin conductance, skin capacitance, water evaporation rate, electrical conductivity, infrared radiation, lactic acid concentration, oleic acid concentration, lipid peroxidation level, skin oxidative stress level, skin anti-oxidant potential, hair coverage condition, sebum production, elasticity, sensitivity, moisture level, pigmentation, scalp scaling I flaking, perifollicular scaling, and porphyrin amount.

5. The method according to any one of claims 1 to 4, wherein the scalp characteristics are stored in a database.

6. The method according to any one of claims 1 to 5, wherein in step b) the at least one scalp characteristic is evaluated by at least one non-invasive imaging technique.

7. The method according to claim 6, wherein the at least one non-invasive imaging technique is selected from the group consisting of dermatoscope, high- resolution photography, thermal camera, ultrasound imaging device, confocal microscopy, and spectrometer.

8. The method according to any one of claims 1 to 7, wherein in step b) the at least one scalp characteristic is evaluated over time to monitor changes.

9. The method according to any one of claims 1 to 8, wherein in step c) each data point of a measured scalp characteristic is integrated into a scalp map by annotating each data point with the corresponding coordinate.

10. The method according to any one of claims 1 to 9, wherein the visual image in step d) is displayed using a technique selected from the group consisting of heat maps, augmented reality overlays and 3D models.

11. The method according to any one of claims 1 to 10, wherein in step e) the analysis of the visual image and measured scalp characteristics is performed by using machine learning algorithms and artificial intelligence models.

12. The method according to any one of claims 1 to 11 , wherein the deficiency and / or medical condition is selected from the group consisting of scalp psoriasis, scalp acne, folliculitis, scalp eczema, seborrheic dermatitis, hair loss, hair thinning, abnormal follicle health, alopecia areata, tinea capitis, traction alopecia, and scalp infections.

13. The method according to any one of claims 1 to 12, wherein in step e) diagnosing comprises identifying early warning signs of potential scalp medical conditions and deficiencies before they become clinically apparent.

14. The method according to any one of claims 1 to 13, wherein the analysis in step e) comprises cross-referencing the measured scalp characteristics with a database of known scalp medical conditions and their characteristics.

15. A system for diagnosing the state of the scalp comprising at least one device for evaluating at least one scalp characteristic using non- invasive imaging techniques, at least one computer for attributing the measured scalp characteristics to the corresponding coordinates, at least one database for storing the information related to the scalp characteristics and the plurality of coordinates, and at least one imaging unit capable of generating a visual image of the scalp based on the measured characteristics and the scalp map coordinates.