Robotics + Healthcare · Public Academic Demo

Dr. NAO

AI-Assisted Dermatology × Robotics

An educational AI and robotics demo integrating a NAO humanoid robot, a web interface, and a pre-trained skin lesion classifier into an interactive workflow.

RoleMain AI/Model & Robot-Integration Contributor

Year2026

StatusPublic Academic Demo

Dr. Nao AI-assisted dermatology and robotics project cover

Educational AI + Robotics Demo

OVERVIEW

AI inference connected to a humanoid-robot workflow.

Dr. Nao is an educational demonstration project that integrates a NAO humanoid robot, a web-based dermatology interface, and a pre-trained skin lesion classification model. The project focuses on the complete interaction flow around the model: image acquisition, backend inference, visual presentation, and NAO-oriented interaction.

CORE WORKFLOW

Three image-input paths, one interactive AI flow.

Image Upload

Analyze a prepared skin-lesion image directly through the web interface.

Laptop Camera

Capture a live image from the computer and route it through the same inference flow.

NAO Camera

Acquire imagery through a NAO-connected camera workflow for robot-assisted demonstrations.

AI Inference

Return an illustrative predicted class, confidence, and ranked alternatives from the integrated pre-trained model.

SYSTEM FLOW

From camera input to robot-assisted explanation.

01AcquireUpload · Laptop camera · NAO camera

02ProcessBackend image handling and preprocessing

03ClassifyPre-trained skin-lesion model inference

04PresentPredicted class · confidence · top alternatives

05InteractNAO-compatible speech / explanation flow

PROJECT GALLERY

Implemented views from the academic prototype.

The screenshots below show the actual web workflow, including uploaded-image analysis, NAO-camera capture, and illustrative prediction outputs.

Dr. Nao home interface — **Home Interface**Entry point for the interactive dermatology and robotics demo.

Dr. Nao image upload and camera selection interface — **Upload & Camera Selection**Choose file, laptop camera, or NAO camera as the image source.

Dr. Nao NAO camera capture workflow — **NAO Camera Capture**Image acquisition through the robot-oriented camera pipeline.

Dr. Nao illustrative Nevus prediction result — **Illustrative Nevus Output**Demo prediction with confidence and ranked alternatives.

Dr. Nao illustrative Basal Cell Carcinoma prediction result — **Illustrative BCC Output**Another example output from the educational workflow.

DEMO VIDEO

The project is best understood in motion.

Watch the interactive workflow connecting the application, AI inference, and NAO-oriented demonstration.

ENGINEERING FOCUS

Integration is the core of the project.

Dr. Nao is primarily a system-integration project. It connects model inference with FastAPI backend components, browser interaction, camera acquisition, and a NAO-compatible interaction path rather than presenting the classifier as an isolated notebook experiment.

Web applicationInteractive browser workflow for image acquisition and result presentation.

Backend servingFastAPI-based components coordinate inference and application communication.

NAO integrationCamera and speech-oriented pathways connect the robot to the demonstration flow.

Demo reliabilityCross-component testing is essential when cameras, AI inference, web UI, and robot interaction must work together.

MODEL ATTRIBUTION

Responsible reuse of a pre-trained model.

The project integrates the pre-trained iamhmh / derm-cnn-ham10000 skin-lesion classifier as part of the academic demo workflow. The original model weights are not redistributed in this repository, and the public project documentation directs users to the upstream source and its licensing terms.

The model and the Dr. Nao application are presented strictly for educational, academic, demonstration-oriented, non-commercial use.

TECH STACK

PythonFastAPIPyTorchNAOComputer Vision

AIPyTorch · pre-trained skin-lesion classifier

BackendPython · FastAPI

FrontendHTML · CSS · JavaScript

RoboticsNAO · NAOqi-oriented integration workflow

VisionImage acquisition · preprocessing · classification

PUBLIC REPOSITORY

Explore the academic demo implementation on GitHub.

View Repository Open Demo Video Back to top