Thesis Project Form

Neurodevelopmental disorders (NDs) represent a significant global health challenge in infancy and early childhood. These conditions can profoundly impair cognitive, emotional, and social development if not addressed early. Although structured screening tools exist, their application in standard pediatric care is limited by time constraints, infrastructure gaps, and the need for specialized expertise. Moreover, current assessments often rely on subjective observations and caregiver reports, which are difficult to standardize and may be insufficient for evaluating young children. These limitations highlight the urgent need for objective, scalable tools to support early screening. In this context, technology-augmented environments equipped with video-based, multimodal sensing systems offer a promising direction. Such systems enable the collection of quantitative, reproducible data in a natural and engaging setting without requiring wearable sensors or intrusive equipment.

The long-term goal of this project is to contribute to the design and development of an interactive environment to support early detection of neurodevelopmental disorders. The system will consist of a controlled physical space where children engage with physical stimuli, such as buttons, lights, and sounds, designed to elicit key motor, attentional, and cognitive behaviours. All interactions will be recorded through cameras, enabling automated, non-invasive video analysis of the child’s behaviour.

Main activities include:

· Prototyping a child-friendly interactive room with interactive objects such as buttons, lights and sounds.

· Selecting, positioning, and integrating multiple cameras and microphones.

· Developing a software framework for synchronized stimulus control and data acquisition

· Conducting pilot tests to assess system feasibility usability, and its ability to capture clinically relevant behavioural patterns.

The thesis will provide experience in:

· hardware–software integration for prototyping interactive environments.

· Applying computer vision techniques such as pose estimation, gaze tracking, and action recognition to analyze video data.

· Configuring and synchronizing multiple video-based sensors for multimodal data acquisition.

· Designing experimental protocols and conducting usability testing with pediatric users in a controlled setting.