Personalising wearable neuroimaging for neurodivergent children through co-design with families and industry

Wearable neuroimaging methods hold considerable promise for identifying early biomarkers of neurodevelopmental conditions, yet their application to neurodivergent young children remains limited by significant participation barriers. We investigated inclusion rates and parental experiences in a combined virtual reality and diffuse optical tomography platform. Fifty-four 3-to-7-year-olds across three groups, neurotypical, elevated likelihood of Attention Deficit Hyperactivity Disorder (ADHD/EL), and autism (Autism/EL, predominantly confirmed diagnoses) were tested twice.

Neurotypical and ADHD/EL children engaged at consistently high rates, with near-ceiling task completion and equipment tolerance. Engagement in the autistic group was markedly more variable, shaped by equipment-related hypersensitivity, particularly the shutter glasses and the cap, that persisted across visits despite targeted adaptations. Parental insights corroborated these findings: anticipated and experienced equipment concerns differed significantly across groups and remained elevated for autistic families throughout both visits.

Signal quality in the autistic group was correspondingly lower and declined between visits, partly attributable to cap loosening for more sensitive children. Drawing on iterative parental co-design and industry partnership, we developed a four-phase personalisation framework covering pre-visit preparation, in-session adaptations, and engagement with device developers. We provide the first evidence base for inclusive wearable neuroimaging in neurodivergent children and a replicable framework for moving the field beyond one-size-fits-all protocols.

We are very grateful to all the children and parents who participated in this study. We thank Vanessa Madeira, Gila Ehrenstein, Klea Malai, Natalie Ellis, Farah Ghosn, Zohreh Soleimani, Reeshu Varna, and the placement and master students of the CBCD for research assistance during the testing sessions. This work was supported by the Engineering and Physical Sciences Research Council (EP/W035154/1) through the Respect4Neurodevelopment network and undertaken at the Centre for Brain and Cognitive Development, Birkbeck, University of London.

C.B. was supported by the Early Career Fellowship Leverhulme Trust (ECF-2021-174). P.P. acknowledges support from the Wellcome Trust (212979/Z/18/Z). Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK Giulia Serino, Paola Pinti & Chiara Bulgarelli Gowerlabs Ltd., Stoneleigh House, Mosslea Road, SE20 7BW, London, UK Department of Medical Physics and Biomedical Engineering, University College London, London, UK Department of Computer Science, Brunel University, London, UK Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK Institute of Cognitive Neuroscience, University College London, London, UK Eirim, The National Assessment Agency, Dublin, Ireland Clinical, Educational, and Health Psychology Research Department, University College London, London, UK This work involves the application of a technology developed by Gowerlabs Ltd, a UCL spin-out company, with which S.P. and N.E. are affiliated.

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