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CDI - Type II: Transforming Community-Based Elder Care through Heterogeneous Activity Sensing Analytics

CDI - Type II: Transforming Community-Based Elder Care through Heterogeneous Activity Sensing Analytics
CDI - II 类:通过异构活动感知分析转变基于社区的老年护理
批准号:
1028195
负责人:
Magdalena Balazinska
金额:
$149.69万
依托单位:
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
项目状态:
已结题
起止时间:
2010-09-15 至 2015-08-31

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中文摘要
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英文摘要
Health care systems face critical challenges as people live longer with multiple chronic conditions that increase their need for health care services. Addressing the needs of an aging population requires improved methods for community-based preventive care through ongoing monitoring, early detection of adverse events and patterns, and early intervention.This project addresses this challenge by developing a transformative pipeline of flexible tools for at-home activity monitoring and analysis. The key goal is to enable at-home deployments of flexible sensor platforms and tools for agile analysis of this sensor data by users with varying skill sets and information needs. To achieve this goal, the project focuses on three specific challenges. First, this project is developing new platforms for deploying different combinations of at-home sensors according to varying elder needs. Second, this project is creating new tools for converting the raw sensor data into knowledge of elder activities and their impact on elder care. This requires rapid organization, analysis, and interpretation of heterogeneous and noisy data across multiple scales of analysis. Finally, the project is developing new techniques to support the varying and unpredictable information needs of all actors involved in elder care: the elders themselves, informal caregivers (e.g., family members), formal caregivers (e.g., community nurses), and health researchers (e.g., evaluating the effectiveness of different prescribed activity regimens).The expected results of this project include (a) new platforms that integrate a variety of heterogeneous home sensors, (b) new streaming data models and query processing techniques addressing the noisy, low-level, and bursty nature of home activity sensing data, (c) new techniques for effective end-user interaction with this data, (d) a system that integrates all three components into a single data acquisition and analysis pipeline, and (e) deep knowledge of how this transformative pipeline can benefit community elder care.Through the above contributions, this project will have broad impact in both computer science and elder care in the United States. The goal is to provide higher quality care at lower cost that keeps elders in their homes longer.
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