CAREER: Learning Visual Representations of Motor Function in Infants as Prodromal Signs for Autism

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。自闭症谱系障碍（ASD）是一种神经发育状况，影响社会沟通和灵活行为，占人口的1.5%。 运动障碍被认为是ASD的第一个迹象之一，可能先于社交或语言异常。 但是，运动质量的差异也与其他疾病有关，如脑瘫和发育协调障碍，因此，虽然早期运动缺陷本身并不能诊断ASD，但它们是风险指标。 这项研究将直接有助于早期识别婴儿的运动缺陷，从而能够早期治疗，从而提高生活质量，降低医疗保健和教育成本。 将来自波多黎各的医疗服务不足、低收入、健康状况不均衡的人口纳入研究，将产生更广泛的影响，这将有助于弥补公共卫生研究的一个重大空白（因为以前的研究主要集中在社会经济地位高的白色人样本上，与历史上被边缘化和处于风险中的社区的相关性有限）。 此外，教育活动将吸引高中到研究生，为未来的数据科学家和工程师创造一个渠道，使他们能够民主地进入更广泛的社区。 为了最大限度地发挥影响，项目成果将在同行评议的文章，推广计划和开放代码/数据repositors.The的目标是建立一个基于计算机视觉的，人工智能指导的婴儿运动功能监测和评估系统，使运动障碍的措施，而婴儿在他们的自然环境中，不引人注目的跟踪。 为此，该研究将学习和量化婴儿运动功能的视觉表征，并开发新的数据/标签高效的人工智能技术，包括生物力学约束的合成数据增强，语义感知域适应和人类-人工智能联合标记算法。 与波多黎各探索污染威胁试验场（Testsite for Exploring Contamination Threats，简称STT）队列的合作，将能够对5-10个月婴儿早期运动功能的提取指标及其与18和24个月时进行的标准化风险筛查试验的关系进行大规模临床验证。 该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social communication and flexible behavior in up to 1.5% of the population. Movement disorders are considered one of the first signs of ASD, and probably precede social or linguistic abnormalities. But differences in motor movement quality are also associated with other conditions, such as Cerebral Palsy and Developmental Coordination Disorder, so while early motor deficits are not in themselves diagnostic of ASD they are risk indicators. This research will directly aid in early identification of motor deficits in infants, thereby enabling early treatment resulting in better quality of life as well as reduced healthcare and education costs. Additional broad impact will derive from inclusion of an underserved, low-income population with health disparities from Puerto Rico, which will help ameliorate a critical public health research gap (since prior studies have focused overwhelmingly on White, high socio-economic status samples, with only limited relevance to historically marginalized and at-risk communities). In addition, educational activities will engage high school through graduate students to create a pipeline of future data scientists and engineers that democratizes access to broader communities. To maximize impact, project outcomes will be disseminated in peer-reviewed articles, outreach programs, and open code/data repositories.The goal of this work is to establish a computer vision-based, artificial intelligence-guided infant motor function monitoring and assessment system to enable unobtrusive tracking of measures of motor impairment while the infant is in their natural environment. To this end, the research will learn and quantify visual representations of motor function in infants and develop novel data/label-efficient AI techniques, including biomechanically constrained synthetic data augmentation, semantic-aware domain adaptation, and human-AI co-labeling algorithms. The collaboration with the Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort will enable large-scale clinical validation of the extracted measures of early motor function in infants between the ages of 5-10 months and their relationship with the standardized risk screening tests performed at 18 and 24 months of age. A public outreach activity presenting live demonstrations of the developed AI tools will help raise awareness of the importance of AI-guided automatic motor function monitoring early in life.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.