ABOUT THIS POSITION

Dutch Youth Healthcare (YHC) routinely monitors the developmental milestones of children aged 0-4 years using the Dutch Development Instrument (DDI), known in Dutch as Van Wiechenonderzoek. YHC professionals observe these milestones during routine visits to track development and identify potential delays due to disorders such as Duchenne Muscular Dystrophy and Developmental Language Disorder. Despite aiming for early detection, the DDI can miss subtle patterns or abnormalities in movement, speech, and language behavior, leading to late identification of developmental delays and missed opportunities for early intervention and treatment. Efforts to address these issues have focused on providing instructional videos for parents. A more advanced solution involves using artificial intelligence (AI) technologies to enable a multi-modal approach, capturing a wider range of digital biomarkers. By applying AI to video and speech data to capture visual (movements) and auditory (sounds) cues, abnormalities are expected to be detected at an earlier stage.

Our previous research explored the attitudes, needs, and concerns of parents, healthcare professionals (including YHC professionals), and YHC managers regarding AI’s use in monitoring children’s development as a prerequisite for its potential successful implementation and usage. The results showed generally positive attitudes towards AI, recognizing its potential to enhance efficiency, support healthcare professionals, and improve monitoring. While AI algorithms for movements and sounds are available, they need further refinement to improve accuracy for detecting developmental disorders.
You will be part of the Child Health team located at TNO in Leiden. You will study how an AI-driven system for early detection of developmental disorders can be used in daily practice by parents, YHC professionals, physiotherapists, speech therapists, clinicians, and other healthcare professionals to detect developmental disorders early by developing and testing a demo. This study aims to provide a conceptual framework of the system’s potential design. It will help to get insight into the entire process, from start to end, and offer insights into the system’s use and technology.
You will work on developing and fine-tuning AI algorithms for movements based on available video data from children with Duchenne Muscular Dystrophy provided by the Duchenne Parent Project and children with normal development provided by TNO.