Unlocking autism’s complexity: the Move Initiative’s path to comprehensive motor function analysis - Ashley Priscilla Good; Elizabeth Horn (Frontiers in Integrative Neuroscience)
The long-standing practice of using manualized inventories and observational assessments to diagnose and track motor function in autism overlooks critical data invisible to the naked eye. This subjective approach can introduce biases and hinder the translation of research into clinical applications that rely on objective markers of brain–body connections. Meanwhile, we are experiencing a digital healthcare revolution, marked by innovations in the collection and analysis of electronic health records, personal genomes, and diverse physiological measurements. Advanced technologies, including current wearable devices, integrate both active and passive (sensor-based) data collection, providing a more comprehensive view of human health. Despite advances in sensors, wearables, algorithms, machine learning, and agentic AI, autism research remains siloed, with many tools inaccessible to affected families and care teams. There is a pressing need to merge these technological advances and expedite their translation into accessible, scalable tools and solutions to diversify scientific understanding. In response, this Perspective introduces the Move Initiative, a coalition spearheaded by the nonprofit 2 m Foundation, composed of self-advocates, families, clinicians, researchers, entrepreneurs, and investors who aim to advance and refine the measurement of movement in autism. Move will make motor screenings more dynamic and longitudinal while supporting continuous assessment of targeted interventions. By fostering cross-disciplinary collaboration, Move seeks to accelerate the integration of the expanding knowledge base into widespread practice. Deep, longitudinal, multi-modal profiling of individuals with Autism Spectrum Disorder offers an opportunity to address gaps in current data and methods, enabling new avenues of inquiry and a more comprehensive understanding of this complex, heterogeneous condition.