SBIR Phase I: Seamless mobile health monitoring platform using novel informatics-based methods

SBIR 第一阶段：使用基于信息学的新型方法的无缝移动健康监测平台

• 批准号: 0945307
• 负责人: Steven LeBoeuf
• 金额: $ 15万
• 依托单位: Valencell Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0945307&HistoricalAwards=false
• 关键词: SBIR; Phase; Seamless; mobile; health

This Small Business Innovation Research (SBIR)Phase I project will demonstrate the feasibility of a wireless, wearable, noninvasive platform for monitoring fitness and health that is virtually unnoticed by the user for maximum performance and convenience. Generating mobile health assessments, such as cardiovascular status, blood pressure, and metabolic activity, requires advanced algorithms that can extract meaningful correlations from orthogonal, low-acuity sensors within a mobile platform. However, commercially available health and fitness monitors cannot generate these assessments during everyday life activities. This limitation is caused by motion-related noise which convolutes sensor data and destroys sensor accuracy and reliability. This Phase I program will demonstrate the feasibility of a novel method for generating mobile health assessments within a mobile platform using machine learning probabilistic models. These models will then be programmed into algorithms that can be implemented in real-time via a single, wearable device in wireless communication with a smartphone. The broader impact/commercial potential of this project will address critical problems across multiple industries. In the consumer fitness markets, mobile fitness assessments will promote healthier lifestyles and enhanced athletic performance. In mobile health (mHealth) markets, mobile health assessments will substantially reduce medical costs through prevention. In the military/first responder market, wireless vital status assessments will enable advanced performance training and maximization of triage resources. For clinical research markets, the mobile platform will enable new scientific studies correlating physiological reactions to new therapies in a real-world environment. Additionally, novel algorithms demonstrated in this Phase I program can eventually be applied towards wireless mortality monitoring in hospitals as well has home health monitoring for the outpatients and the elderly.

这项小型企业创新研究（SBIR）I阶段项目将证明无线，可穿戴，无创的平台用于监测健身和健康，该平台几乎没有被用户注意，以提供最大的性能和便利性。产生移动健康评估，例如心血管状态，血压和代谢活动，需要高级算法，这些算法可以从移动平台内的正交，低额度传感器中提取有意义的相关性。但是，在日常生活活动中，市售的健康和健身监视器无法产生这些评估。该限制是由与运动相关的噪声引起的，该噪声会使传感器数据加注并破坏传感器的准确性和可靠性。该阶段I计划将证明使用机器学习概率模型在移动平台内生成移动健康评估的新方法的可行性。然后，这些模型将被编程为算法，这些算法可以通过与智能手机无线通信实时实时实现。 该项目的更广泛的影响/商业潜力将解决多个行业的关键问题。在消费者健身市场中，移动健身评估将促进更健康的生活方式并提高运动表现。在移动健康（MHealth）市场中，移动健康评估将通过预防大大降低医疗费用。在军事/第一响应者市场中，无线生命状况评估将使高级绩效培训和分类资源的最大化。 对于临床研究市场，移动平台将使新的科学研究能够将生理反应与现实环境中的新疗法相关联。此外，在此I期计划中证明的新算法最终可以用于医院的无线死亡率监测，还可以对门诊病人和老年人进行家庭健康监测。