This project examines the core video-based infant movement analysis using advanced Computer Vision and Machine Learning models to improve the performance of the clinical decision support tool, as well as how the patient data collected from different teams  can be used in the ‘Regulatory Sandbox’ as real-world data to test the robustness of AI models.

 The interdisciplinary team shares a common interest in analysing infant movements using AI and the collaboration will benefit by sharing knowledge in different areas, including AI, Clinical, Data Security and Governance, and Commercialisation.

The planned outcome of this ICF award is to consolidate the core directions in the proposal and the project team. It is expected that upon completion of this award, collaborators will complete the ERC funding proposal which by inviting a wider group of partners and forming a bigger team to strengthen the proposal.