Hemiplegia due to stroke is a common condition in childhood, affecting up to 1 child in 1,000 life birth with a severe impact on children’s quality of life. CATCH-HEMI aims to change the current management of these children by identifying relevant biomarkers of four different areas (omics, clinical, neuroimaging, digital data) to create a novel transdisciplinary patient-centred model to optimize and tailor their rehabilitation treatment. The feasibility of CATCH-HEMI approach will be applied for deeply analysing big data and understanding results of previous researches and in new pilot studies on already available rehabilitative treatments. The results will provide an example of how different kinds of biomarkers can contribute to create a plan for the management of children with hemiplegia, thus leading to a better understanding of the correlation between genetic and phenotypic data. The Health Technology Assessment will provide estimates of its national and regional cost effectiveness.