SCH:INT: SCH: INT: A gamified mobile system for real-time mental health data modeling and personalized autism care across sociocultural settings

SCH:INT: SCH:INT：一个游戏化的移动系统，用于跨社会文化环境的实时心理健康数据建模和个性化自闭症护理

• 批准号: 2014232
• 负责人: Dennis Wall
• 金额: $ 110.01万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014232&HistoricalAwards=false
• 关键词: SCH; INT; gamified; mobile; system

Neuropsychiatric disorders are the single greatest cause of disability due to non-communicable disease worldwide, accounting for as much as 19% of the global burden of disease. These disorders include autism spectrum disorder, which is among the fastest growing pediatric concerns today and highly representative of many other neuropsychiatric conditions. The current standards of care for neuropsychiatric disorders are negatively impacted by subjectivity, inconsistent delivery, and limited access as waiting lists grow. New informatics solutions, in particular artificial intelligence (AI), that can port to more ubiquitous mobile health devices and that are not restricted for use in clinical settings, have great potential to complement the current standards of care. With this research project, a novel digital support for autism will be developed. Specifically, working together with families and their affected children ages 2-8, we will establish a gaming system for mobile devices. This system will use augmented reality and AI to adapt to the child’s needs and foster a social exchange between the primary caregiver and the child. This mobile solution will connect families to care, fostering the development of a community of stakeholders, together with AI models capable of personalizing care and tracking progress.This project will: (1) combine human-computer-interaction with clinically validated treatment approaches through iterative co-design with affected children and their families; (2) identify at least three promising augmented reality game modes that address core autism features including social-reciprocity and emotional understanding; (3) lower barriers to secure and trustworthy data sharing by game players; and (4) construct a series of AI models from game play data that can be used to understand and dynamically react to the treatment effect during game play. Our research project will result in an engaging at-home digital tool accessible to any family with a smartphone (iOS or Android). The project will show how this mobile AI solution can act as a scalable supplement to standard therapy and one that has the potential to reduce the healthcare burden by empowering caregivers. Finally, the research will generate solutions, code, examples, and computer vision libraries that will enable the development of a broader platform for AI in the mobile environment in socioeconomically diverse populations and set the stage for similar solutions for other mental health conditions.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.

神经精神障碍是全球非传染性疾病导致残疾的最大原因，占全球疾病负担的19%。这些疾病包括自闭症谱系障碍，这是当今增长最快的儿科问题之一，也是许多其他神经精神疾病的高度代表。随着等待名单的增加，目前对神经精神疾病的护理标准受到主观性、不一致的交付和有限的访问的负面影响。新的信息学解决方案，特别是人工智能（AI），可以移植到更普遍的移动的医疗设备，并且不限于在临床环境中使用，具有很大的潜力来补充当前的护理标准。通过这个研究项目，将开发一种新的自闭症数字支持。具体来说，我们将与家庭及其2-8岁的受影响儿童合作，建立一个适用于移动的设备的游戏系统。该系统将使用增强现实和人工智能来适应孩子的需求，并促进主要照顾者和孩子之间的社交交流。 这个移动的解决方案将连接家庭和护理，促进利益相关者社区的发展，以及能够个性化护理和跟踪进展的人工智能模型。该项目将：（1）通过与受影响儿童及其家庭的迭代共同设计，将联合收割机与临床验证的治疗方法相结合;（2）确定至少三种有前途的增强现实游戏模式，解决核心自闭症特征，包括社会互惠和情感理解;（3）降低游戏玩家安全和可信数据共享的障碍;以及（4）从游戏数据构建一系列AI模型，其可用于理解游戏期间的治疗效果并对其作出动态反应。 我们的研究项目将产生一个有吸引力的家庭数字工具，任何家庭都可以使用智能手机（iOS或Android）。该项目将展示这种移动的人工智能解决方案如何作为标准治疗的可扩展补充，以及通过赋予护理人员权力来减轻医疗负担的潜力。最后，研究将生成解决方案，代码，示例，和计算机视觉库，这将使在社会经济多样化的人群中的移动的环境中开发更广泛的人工智能平台，并为其他心理健康状况的类似解决方案奠定基础。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进行评估，被认为值得支持审查标准。

项目成果

Labeling images with facial emotion and the potential for pediatric healthcare

• DOI: 10.1016/j.artmed.2019.06.004
• 发表时间: 2019-07-01
• 期刊: ARTIFICIAL INTELLIGENCE IN MEDICINE
• 影响因子: 7.5
• 作者: Kalantarian, Haik;Jedoui, Khaled;Wall, Dennis P.
• 通讯作者: Wall, Dennis P.

Activity Recognition with Moving Cameras and Few Training Examples: Applications for Detection of Autism-Related Headbanging

• DOI: 10.1145/3411763.3451701
• 发表时间: 2021-01
• 期刊: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
• 作者: P. Washington;A. Kline;O. Mutlu;É. Leblanc;C. Hou;N. Stockham;K. Paskov;B. Chrisman;D. Wall

A Mobile Game Platform for Improving Social Communication in Children with Autism: A Feasibility Study.

• DOI: 10.1055/s-0041-1736626
• 发表时间: 2021-10
• 期刊: Applied clinical informatics
• 影响因子: 2.9
• 作者: Penev Y;Dunlap K;Husic A;Hou C;Washington P;Leblanc E;Kline A;Kent J;Ng-Thow-Hing A;Liu B;Harjadi C;Tsou M;Desai M;Wall DP
• 通讯作者: Wall DP

Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels.

• DOI: 10.1007/s12559-021-09936-4
• 发表时间: 2021-09
• 期刊: COGNITIVE COMPUTATION
• 影响因子: 5.4
• 作者: Washington, Peter;Kalantarian, Haik;Kent, Jack;Husic, Arman;Kline, Aaron;Leblanc, Emilie;Hou, Cathy;Mutlu, Cezmi;Dunlap, Kaitlyn;Penev, Yordan;Stockham, Nate;Chrisman, Brianna;Paskov, Kelley;Jung, Jae-Yoon;Voss, Catalin;Haber, Nick;Wall, Dennis P.
• 通讯作者: Wall, Dennis P.

The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study

• DOI: 10.2196/13174
• 发表时间: 2020-04-01
• 期刊: JMIR MENTAL HEALTH
• 影响因子: 5.2
• 作者: Kalantarian, Haik;Jedoui, Khaled;Wall, Dennis Paul
• 通讯作者: Wall, Dennis Paul