R-001-008 Legit.Health Plus label for Brazil

Label

• Device name: Legit.Health Plus
• European Medical Device Nomenclature (EMDN) coding: Z12040192 (General medicine diagnosis and monitoring instruments - Medical device software)
• Global Medical Device Nomenclature (GMDN) coding: 65975
• Risk Classification according to RDC No. 751: Class II
• ANVISA registration number: Pending
• Authorised Representative: Brazil Import Healthcare Solutions Av. Octávio Gama, 1057, Bloco 19, 1901, 23.970-000, Caborê, Paraty, Rio de Janeiro (Brazil)
• Technical Responsible Person: Claudia Carolina de Carvalho Mayer CRF/RJ 28.046

Symbol	Meaning	Information
	Unique Device Identifier	(01)UDI-DI(10)1.0.0.0(11)YYYYMMDD
	Version	(10) 1.0.0.0
	Manufacture date	(11) YYYYMMDD
	Manufacturer	AI Labs Group SL, BAT Tower, Gran Vía 1, 48001, Bilbao, Biscay (Spain)

Symbol	Meaning
eIFU	Read the instructions before use
	In case of observing an incorrect operation of the software, notify the manufacturer as soon as possible: support@ legit.health. The manufacturer will proceed accordingly. Any serious incident should be reported to AI Labs Group S.L. as well as to the National Competent Authority of the country.
	Medical Device

Undesirable side-effects

It is not known or foreseen any undesirable side-effects specifically related to the use of the software.

Intended purpose

Intended use

The device is a computational software-only medical device leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures, enhancing efficiency and accuracy of care delivery, by providing:

• an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image
• quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others

Quantification of intensity, count and extent of visible clinical signs

The device provides quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others; including, but not limited to:

• erythema,
• desquamation,
• induration,
• crusting,
• xerosis (dryness),
• swelling (oedema),
• oozing,
• excoriation,
• lichenification,
• exudation,
• wound depth,
• wound border,
• undermining,
• hair loss,
• necrotic tissue,
• granulation tissue,
• epithelialization,
• nodule,
• papule
• pustule,
• cyst,
• comedone,
• abscess,
• draining tunnel,
• inflammatory lesion,
• exposed wound, bone and/or adjacent tissues,
• slough or biofilm,
• maceration,
• external material over the lesion,
• hypopigmentation or depigmentation,
• hyperpigmentation,
• scar,
• ictericia

Image-based recognition of visible ICD categories

The device is intended to provide an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

Device description

The device is a computational software-only medical device leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures. Its principal function is to provide a wide range of clinical data from the analyzed images to assist healthcare practitioners in their clinical evaluations and allow healthcare provider organisations to gather data and improve their workflows.

The generated data is intended to aid healthcare practitioners and organizations in their clinical decision-making process, thus enhancing the efficiency and accuracy of care delivery.

The device should never be used to confirm a clinical diagnosis. On the contrary, its result is one element of the overall clinical assessment. Indeed, the device is designed to be used when a healthcare practitioner chooses to obtain additional information to consider a decision.

Intended medical indication

The device is indicated for use on images of visible skin structure abnormalities to support the assessment of all diseases of the skin incorporating conditions affecting the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

Intended patient population

The device is intended for use on images of skin from patients presenting visible skin structure abnormalities, across all age groups, skin types, and demographics.

Intended user

The medical device is intended for use by healthcare providers to aid in the assessment of skin structures.

User qualifications and competencies

This section outlines the qualifications and competencies required for users of the device to ensure its safe and effective use. It is assumed that all users already possess the baseline qualifications and competencies associated with their respective professional roles.

Healthcare professionals

No additional official qualifications are required for healthcare professionals (HCPs) to use the device. However, it is recommended that HCPs possess the following competencies to optimize device utilization:

• Proficiency in capturing high-quality clinical images using smartphones or equivalent digital devices.
• Basic understanding of the clinical context in which the device is applied.
• Familiarity with interpreting digital health data as part of the clinical decision-making process.

The device may be used by any healthcare professional who, by virtue of their academic degree, professional license, or recognized qualification, is authorized to provide healthcare services. This includes, but is not limited to:

• Medical Doctors (MD, MBBS, DO, Dr. med., or equivalent)
• Registered Nurses (RN, BScN, MScN, Dipl. Pflegefachfrau/-mann, or equivalent)
• Nurse Practitioners (NP, Advanced Nurse Practitioner, or equivalent)
• Physician Assistants (PA, or equivalent roles such as Physician Associate in the UK/EU)
• Dermatologists (board-certified, Facharzt für Dermatologie, or equivalent)
• Other licensed or registered healthcare professionals as recognized by local, national, or European regulatory authorities

Each HCP must hold the academic title, degree, or professional registration that confers their status as a healthcare professional in their jurisdiction, whether in the United States, Europe, or other regions where the device is provided.

IT professionals

IT professionals are responsible for the technical integration, configuration, and maintenance of the medical device within the healthcare organization's information systems.

No specific official qualifications are mandated. Nevertheless, it is advisable that IT professionals involved in the deployment and support of the device have the following competencies:

• Foundational knowledge of the HL7 FHIR (Fast Healthcare Interoperability Resources) standard and its application in healthcare data exchange.
• Ability to interpret and manage the device's data outputs, including integration with electronic health record (EHR) systems.
• Understanding of healthcare data privacy and security requirements relevant to medical device integration, including GDPR (Europe), HIPAA (US), and other applicable local regulations.
• Experience with troubleshooting and supporting clinical software in a healthcare environment.
• Familiarity with IT standards and best practices for healthcare, such as ISO/IEC 27001 (Information Security Management) and ISO 27799 (Health Informatics—Information Security Management in Health).

IT professionals may include, but are not limited to:

• Health Informatics Specialists (MSc Health Informatics, or equivalent)
• Clinical IT System Administrators
• Healthcare Integration Engineers
• IT Managers and Project Managers in healthcare settings
• Software Engineers and Developers specializing in healthcare IT
• Other IT professionals with relevant experience in healthcare environments, as recognized by local, national, or European authorities

Each IT professional should possess the relevant academic degree, professional certification, or demonstrable experience that qualifies them for their role in the healthcare organization, in accordance with the requirements of the United States, Europe, or other regions where the device is provided.

Use environment

The device is intended to be used in the setting of healthcare organisations and their IT departments, which commonly are situated inside hospitals or other clinical facilities.

The device is intended to be integrated into the healthcare organisation's system by IT professionals.

Operating principle

The device is computational medical tool leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures.

Body structures

The device is intended to use on the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

In fact, the device is intended to use on visible skin structures. As such, it can only quantify clinical signs that are visible, and distribute the probabilities across ICD categories that are visible.

Explainability

For visual signs that can be quantified in terms of count and extent, the underlying models not only calculate a final value, such as the number of lesions, but also determine their locations within the image. Consequently, the output for these visual signs is accompanied by additional data, which varies depending on whether the quantification involves count or extent.

• Count. When a visual sign is quantifyed by counting, the device generates bounding boxes for each detected entity. These bounding boxes are defined by their x and y coordinates, as well as their height and width in pixels.
• Extent. When a visual sign is quantifyed by its extent, the device outputs a mask. This mask, which is the same size as the image, consists of 0's for pixels where the visual sign is absent and 1's for pixels where it is present.

The explainability output can be found with the explainabilityMedia key. Here is an example:

{
  "explainabilityMedia": {
    "explainabilityMedia": {
      "content": "base 64 image",
      "detections": [
        {
          "confidence": 98,
          "label": "nodule",
          "p1": {
            "x": 202,
            "y": 101
          },
          "p2": {
            "x": 252,
            "y": 154
          }
        },
        {
          "confidence": 92,
          "label": "pustule",
          "p1": {
            "x": 130,
            "y": 194
          },
          "p2": {
            "x": 179,
            "y": 245
          }
        }
      ]
    }
  }
}

Signature meaning

The signatures for the approval process of this document can be found in the verified commits at the repository for the QMS. As a reference, the team members who are expected to participate in this document and their roles in the approval process, as defined in Annex I Responsibility Matrix of the GP-001, are:

• Author: Team members involved
• Reviewer: JD-003, JD-004
• Approver: JD-001