SBIR Phase I: Early Detection and Prediction of Mobility and Cognitive Decline

SBIR 第一阶段：早期检测和预测行动能力和认知能力下降

• 批准号: 2013985
• 负责人: Baturalp Arslan
• 金额: $ 22.5万
• 依托单位: INTHEPENDANT, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2013985&HistoricalAwards=false
• 关键词: SBIR; Phase; Early; Detection; Prediction

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve early detection of cognitive decline and fall risk, particularly in the elderly. The proposed project will develop an artificial intelligence system to assess cognitive issues and estimate how likely a subject is to fall, enabling a new level of security for a vulnerable population.This Small Business Innovation Research (SBIR) Phase I project advances early detection of mobility problems and cognitive decline. This will be accomplished through the development of machine learning algorithms assessing gait dynamics (with dual-task information) in habitual settings. Research objectives include: (1) Developing a machine learning algorithm for fall prediction, (2) Developing preliminary mobility and fall prediction scoring system, (3) Estimating the cognitive state, and (4) Developing an accurate automatic fall detection system.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.

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是改善认知能力下降和跌倒风险的早期检测，特别是在老年人中。 拟议的项目将开发一个人工智能系统，以评估认知问题，并估计一个对象是如何可能会下降，使一个新的安全水平为弱势群体。这个小企业创新研究（SBIR）第一阶段项目推进早期检测的流动性问题和认知能力下降。这将通过开发机器学习算法来实现，该算法评估习惯设置中的步态动力学（具有双任务信息）。研究目标包括：（1）开发用于跌倒预测的机器学习算法，（2）开发初步的移动性和跌倒预测评分系统，（3）评估认知状态，（4）开发准确的自动跌倒检测系统。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。