STTR Phase I: 24x7 mobile wireless monitoring of patient's vitals to proactively manage disease recovery

这个小企业技术转让（STTR）第一阶段项目的更广泛的影响/商业潜力是在拟议的技术开发中发现的，该技术开发有助于直接、无处不在地获取关键生物医学数据，很少或没有人为干预或引入错误，有可能降低医疗保健成本，并在整个社会中彻底改变医疗保健服务。随着智能手机和平板电脑等移动的计算平台的出现，并最终依赖于现成的或内置的传感器，21世纪世纪可能预示着一个时代，健康维护？占主导地位？医疗？持续的24 x7监测也可以促进更个性化的时间衍生医学的概念，从一个显着的变化？的基线状态是否提供了医疗状况的早期预警？而不是确定偏离人口平均水平，或等待症状变得严重。随着广泛使用，这项技术以及患者监测的固有自动化水平可以实现慢性疾病的早期检测，从而显着降低死亡率，发病率和整体医疗成本。关键是，这个STTR团队？的方法有可能扩大医疗保健到各种农村和其他服务不足的社区，使低成本版本的这种技术平台可用，并与已经安装了大量的个人，移动的计算平台，如病人？拥有自己的智能手机和数字蜂窝网络基础设施。拟议的项目将在几个方面大大推进知识。首先，这支STTR球队？的研究涉及医疗保健组织将告知我们一个适当的商业模式，将数字健康信息基础设施（DHII）类型的技术，否则非常复杂的医疗保健市场。它还将提供有关哪些DHII功能是关键的，不重要的，并激励采用这种系统的信息。这是开发新医疗技术时经常被忽视的关键信息。这个STTR团队？的第一阶段研究还将扩大对硬件和软件平台的广义监控限制的理解，以确定需要算法优化以实现更高性能水平的领域。预计来自多个传感器的无线数据流将需要实施数据优化和算法分类协议，以确保获得关键信息内容并可用于车载计算机辅助诊断的本地分析。这些数据也将通过档案存储，在通过传统或云计算架构实施的互联网连接的数据储存库中进行搜索和检索。

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is found in the proposed technology development that facilitates direct, ubiquitous acquisition of key biomedical data, with little or no human intervention or introduction of errors, has the potential to reduce the costs of healthcare and to revolutionize healthcare delivery throughout our society. With readily available mobile computing platforms such as smartphones and tablets, and eventually relying on readily available or built-in sensors, the 21st century could herald an era where ?wellness maintenance? predominates over ?medical care?. Ongoing 24x7 monitoring could also facilitate the concept of more personalized time-derivative medicine, where significant changes from one?s own baseline state provide early warnings of a medical condition?rather than identifying departures from population averages, or waiting for symptoms to become severe. With widespread use, this technology, and the inherent level of automation of patient monitoring, could enable early detection of chronic disease, thereby significantly reducing mortality, morbidity and overall healthcare costs. Critically, this STTR team?s approach has the potential to expand healthcare to various rural and other underserved communities by making low-cost versions of this technology platform available and compatible with an already large installed base of personal, mobile computing platforms such as the patient?s own smartphone and digital cellular network infrastructure. The proposed project will significantly advance knowledge on several fronts. First, this STTR team?s research involving healthcare organizations will inform us of an appropriate business model for introducing Digital Health Information Infrastructure (DHII) type technologies to the otherwise very complex healthcare marketplace. It will also provide information about which DHII features are critical, unimportant, and motivating for adoption of such systems. This is key and often-overlooked information when developing new medical technologies. This STTR team?s Phase I research will also expand the understanding about the limits of generalized monitoring across hardware and software platforms to identify areas where algorithmic optimization is needed to achieve higher levels of performance. Expectations are that the wireless data streaming from multiple sensors will require the implementation of data optimization and algorithmic triage protocols to ensure that critical information content is acquired and available for local analysis by on-board computer-aided diagnostics. This data will also be accessible through archival storage, with search and retrieval, at the internet-connected data repository implemented through traditional or cloud computing architectures.