I-Corps: Mobile Phone Based Vital Sign Detection

I-Corps项目的更广泛的影响/商业潜力包括开发一种可获得的、基于证据的生物反馈干预措施，使患有精神健康障碍的个人能够立即获得有效的治疗。第一个使用案例是大约11%的美国人反复经历恐慌症发作，这会带来巨大的社会成本，使这些人更有可能去急诊室，错过工作，并经历随后的共病。这部分人口目前获得循证治疗的机会有限，因为等待治疗的名单很长，而且提供的治疗往往无效。拟议的数字治疗技术旨在通过在智能手机上提供即时、廉价、循证的干预来满足这一未得到满足的需求。这项技术取得的进展可以扩展到为其他心理健康问题提供生物反馈干预，包括普遍焦虑、创伤后应激障碍、药物滥用障碍，甚至慢性疼痛。这个i-Corps项目开发了新的方法，从手机视频中表征生理状态，并在最需要的地方和时间提供个性化治疗。新的计算算法利用机器学习来实现对生理信号的准确估计，这些信号对日常生活中进行的测量中固有的不完美的数据质量是稳健的。这项技术也可能在情绪高度反应的时候使用。这个项目建立在临床测量和干预方面的创新之上，通过将算法集成到移动应用程序中，使用它来收集真实世界痛苦的数据集，并提供个性化干预信息。该工具的可行性已被证明是一种治疗恐慌发作的数字疗法。该项目将探索这种方法的商业化潜力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project involves the development of an accessible, evidence-based, biofeedback intervention to allow individuals suffering with mental health disorders to have immediate access to effective treatment. A first use case is for the approximately 11% of Americans who experience reoccurring panic attacks, which has significant societal cost such that these individuals are more likely to visit emergency rooms, miss work, and experience subsequent comorbidity. This segment of the population currently has limited access to evidence-based treatment due to long therapy waitlists and often ineffective offerings. The proposed digital therapeutic technology aims to answer this unmet need by providing immediate, inexpensive, evidence-based intervention available on a smartphone. Advances made with this technology could be expanded to also inform biofeedback intervention for other mental health problems including general anxiety, post-traumatic stress disorder, substance abuse disorders, and even chronic pain.This I-Corps project develops new approaches for characterizing physiological states from mobile phone videoes and delivering personalized therapies where and when they are most needed. The novel computational algorithms leverage machine learning to enable accurate estimations of physiological signals that are robust to imperfect data quality inherent in measurements made during daily life. The technology may also be feasible for use during episodes of high emotional reactivity. This project builds on innovations in the clinical measurement and intervention by integrating algorithms into a mobile application, using it to collect datasets of real-world suffering and to inform personalized interventions. The feasibility of the tool has been demonstrated as a digital therapeutic for panic attacks. This project will explore the commercialization potential of this approach.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.