A Wearable, Biomarker-Tracking Device Platform Using Machine Learning and Predictive Technology for Positive Behavior Change.

项目概要/摘要 Behaivior正在开发一个正在申请专利的平台，以预测和预防成瘾复发， 通过使用可穿戴设备（如 先进的FitBit）和人工智能。在真实的时间知道当有人与阿片类药物使用 疾病复发的高风险彻底改变了在正确时刻进行干预的能力， 帮助人们保持清醒我们的研究将有助于了解 需要收集具体信息，以便准确检测某人何时 患有阿片类药物使用障碍的患者处于高风险阿片类药物渴望/痴迷状态， 建立一个及时干预的预测模型。阿片类药物死亡人数 过量每天都在增加，因此减少阿片类药物成瘾复发将挽救生命， 这将减少重新逮捕，重新监禁和重新住院。超过2300万 美国人对毒品和酒精上瘾，这些成瘾花费了美国4420亿美元 根据美国卫生局局长办公室的数据，大多数治疗工具用于 让那些处于恢复期的人保持清醒的成功率很低或好坏参半。很多康复中的人 多次复吸，海洛因复吸率约为90%。利用我们 正在发展，Behaivior将检测是否有人在恢复是在一个红色警报渴望或 “痴迷”状态，然后，使用人工智能，我们将提供支持，在真实的时间， 将某人连接到支持网络成员和/或提供定制的数字 干预 这个I-Corps项目的更广泛的影响/商业潜力围绕着人类 大脑对有害于人类健康和福祉的物质的倾向，如 危险量的糖、盐和药物，这正在造成全球健康和安全风险。 无法避免这些诱惑会缩短寿命，增加医疗成本，并使 资源该团队使用机器学习和模式识别AI来识别和应对 导致人类破坏性行为的因素。虽然最初的重点是阿片类药物，但 在随后的迭代中，无监督学习AI可以用于识别和应对任何 行为-如不安全驾驶，暴饮暴食，或愤怒管理。帮助人们识别 它们行为的前体可以作为一种生物反馈， 支持网络及时和个性化的见解，预防和干预，导致 在许多人群中的成本和健康效益。

Project Summary/Abstract Behaivior is developing a patent-pending platform to predict and prevent addiction relapses and overdoses by treating those in recovery with timely interventions using wearables (like an advanced FitBit) and artificial intelligence. Knowing in real time when someone with opioid use disorder is at a high risk of relapsing revolutionizes the ability to intervene at the right moment to help people stay sober. Our research will contribute to fundamental knowledge about the specific information needed to be gathered in order to accurately detect when someone struggling with opioid use disorder is in a high risk opioid craving/obsession state and enabled the creation of a predictive model for just in time intervention. The number of deaths from opioid overdose is increasing every day, so reducing opioid addiction relapses will save lives and families and it will reduce rearrests, reincarcerations, and rehospitalizations. Over 23 million Americans are addicted to drugs and alcohol, and these addictions cost the U.S. $442 billion per year, according to the US Surgeon General’s office. The majority of treatment tools used to keep those in recovery sober have low or mixed success rates. Many people in recovery end up relapsing multiple times, with the heroin relapse rate around 90%. With the technology that we are developing, Behaivior will detect if someone in recovery is in a red alert craving or “obsession” state and then, using artificial intelligence, we will provide support in real time by connecting someone to a support network member and/or provide a customized digital intervention. The broader impact/commercial potential of this I-Corps project revolves around the human brain’s proclivity towards substances detrimental to human health and wellbeing, such as dangerous amounts of sugar, salt, and drugs, which is causing global health and safety risks. Inability to avoid these temptations shortens lifespans, increases healthcare costs, and strains resources. This team uses machine learning and pattern recognition AI to identify and react to factors that result in destructive human behaviors. While the initial focus is opioids, this unsupervised learning AI could, in subsequent iterations, be used to identify and react to any behavior -- such as unsafe driving, binge eating, or anger management. Helping people identify the precursors to their behaviors could serve as a type of biofeedback that gives them and their support networks timely and individualized insights, preventions, and interventions, resulting in cost and health benefits across many populations.