Signal processing algorithms for interpreting multi-dimensional ambulatory data during normal activities: correlates of current measures of fall risk

用于解释正常活动期间多维动态数据的信号处理算法：当前跌倒风险测量的相关性

• 批准号: DP130102392
• 负责人: A/Prof Stephen Redmond
• 金额: $ 23.42万
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2013
• 资助国家: 澳大利亚
• 起止时间: 2013-01-01 至 2017-06-01
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP130102392
• 关键词: Signal; processing; algorithms; interpreting; multi

This project will develop algorithms to analyse human movement, measured using a small waist-worn sensor, which approximate existing clinical tests to identify likely fallers. This will enable future fall risk monitor development. This is an important problem as one in three senior citizens fall each year, costing around $500 million in healthcare.

该项目将开发算法来分析人体运动，使用一个腰部佩戴的小型传感器来测量，这种传感器近似于现有的临床测试，以识别可能的跌倒。这将使未来的跌倒风险监测发展成为可能。这是一个重要的问题，因为每年每三名老年人中就有一人摔倒，导致医疗保健成本约为5亿美元。