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PhD Forum: Multimodal IoT and EMR Based Smart Health Application for Asthma Management in Children

机译：PHD论坛：用于儿童哮喘管理的多峰IOT和EMR智能健康应用

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According to a study done in 2014 by National Health Interview Survey around 6.3 million children in United States suffer from asthma [1]. Asthma remains one of the leading reasons for pediatric admissions to children's hospitals, and has a prevalence rate of approximately 10% in children and it leads to missed days from school and other societal costs. This occurs despite improved medications to control asthma symptoms. Asthma management is challenging as it involves understanding asthma causes and avoiding asthma triggers that are both multi- factorial and individualistic in nature. It is almost impossible for doctors to constantly monitor each patient's health and environmental triggers. According to a recent article, the IoT device market in health-care will increase to a worth of 15 billion in 2017 [5]. The sales of smart watches, fitness and health trackers, are expected to account for more than 70% of all wearables sale worldwide in 2016 [6]. According to IBM, the volume of health-care data has reached to 150 exabytes in 2017 [7]. The data generated from these consumer graded devices is increasing day by day. This data collection has exacerbated the problem of understanding the data and making sense of it. We can use these low-cost sensors and consumer graded devices for continuous monitoring and management of asthma patients. We developed kHealth, a framework for continuous monitoring of the patient's personal, public and population-based health signals and send alerts to the patient when a condition deserves patient's or clinician's attention. This can assist the clinician in determining the triggers and deciding the future course of action for prevention and treatment of the disease. More importantly, it can also help a patient to better take control of his/her health management by taking more timely actions(e.g., in case of asthma, using an inhaler in a more timely manner to ward off an attack). Our kHealth framework goes well beyond the efforts of data collection and focuses on contextual and personalized processing of multi-modal data to help understand asthma control level and vulnerability score (change in conditions that increases the chances of an adverse event, thus requiring proactive action). Another unique aspect of our research is close collaboration with clinician combined with on-going evaluation of clinician's at the Dayton Children's hospital which involves an ongoing trial of our novel technical approach with a cohort of 200 patients.
机译：根据2014年通过国家卫生访谈调查进行的一项研究，美国约有630万儿童患有哮喘[1]。哮喘仍然是儿童医院儿科招生的主要原因之一，并且儿童的患病率约为10 ％，而且它导致学校和其他社会成本中错过的日子。尽管改善了药物以控制哮喘症状，但这发生这种情况。哮喘管理是挑战，因为它涉及理解哮喘的原因并避免哮喘触发，这是本质上的多因素和个人主义。医生几乎不可能不断监控每位患者的健康和环境触发器。据最近的一篇文章称，2017年医疗保健的物联网设备市场将增加到150亿的价值[5]。智能手表，健身和健康跟踪人员的销售预计将于2016年全球销售超过70 ％的所有可用性地销售[6]。根据IBM，2017年医疗保健数据的体积已达到150个exabytes [7]。从这些消费者分级设备生成的数据日复现。此数据收集加剧了了解数据和理解它的问题。我们可以使用这些低成本传感器和消费者分级设备进行哮喘患者的连续监测和管理。我们开发了Khealth，该框架，持续监测患者的个人，公共和人口的健康信号，并在条件值得患者或临床医生的注意时向患者发送警报。这可以帮助临床医生确定触发器并决定未来的预防和治疗疾病的行动方案。更重要的是，它还可以帮助患者通过更多及时的行动来更好地控制他/她的健康管理（例如，在哮喘的情况下，使用吸入器更及时地使用吸入器来避开攻击）。我们的KHealth框架远远超出了数据收集的努力，并专注于对多模态数据的语境和个性化处理，以帮助了解哮喘控制水平和漏洞得分（在增加不良事件机会的情况下的变化，因此需要主动行动） 。我们研究的另一个独特方面是与临床医生的紧密合作，结合临床医生在顿儿童医院的临床评估，该医院涉及我们具有200名患者队列的新技术方法的持续试验。

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