Opening up the Design Space of Neurofeedback Brain-Computer Interfaces for Children

Brain-computer interface applications (BCIs) utilizing neurofeedback (NF) can make invisible brain states visible in real time. Learning to recognize, modify, and regulate brain states is critical to all children’s development and can improve learning, and emotional and mental health outcomes. How can we design usable and effective NF BCIs that help children learn and practice brain state self-regulation? Our contribution is a list of challenges for this emerging design space and a conceptual framework that addresses those challenges. The framework is composed of five interrelated strong concepts that we adapted from other design spaces. We derived the concepts reflectively, theoretically and empirically through a design research process in which we created and evaluated a NF BCI, called Mind-Full, designed to help children living in Nepal who had suffered from complex trauma learn to self-regulate anxiety and attention. We add rigor to our derivation methodology by horizontally and vertically grounding our concepts, that is, relating them to similar concepts in the literature and instantiations in other artefacts. We illustrate the generative power of the concepts and the inter-relationships between them through the description of two new NF BCIs we created using the framework for urban and indigenous children with anxiety and attentional challenges. We then show the versatility of our framework by describing how it inspired and informed the conceptual design of three NF BCIs for different types of self-regulation: selective attention and working memory, pain management, and depression. Lastly, we discuss the contestability, defensibility and substantiveness of our conceptual framework in order to ensure rigour in our research design process. Our contribution is a rigorously derived design framework that opens up this new and emerging design space of NF BCI’s for children for other researchers and designers.