SHB: Small: Collaborative Research: Electronic Textiles for Ambulatory Health Monitoring

SHB：小型：合作研究：用于动态健康监测的电子纺织品

• 批准号: 1116669
• 负责人: Thomas Martin
• 金额: $ 30.61万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1116669&HistoricalAwards=false
• 关键词: SHB; Small; Collaborative; Research; Electronic

Ambulatory health monitoring has been demonstrated to provide significant benefits to patients in a number of studies. The biggest promise for improved results for patients lies in the long-term, ambulatory monitoring of patients with chronic illnesses to help doctors and patients identify health issues before they reach a crisis stage. This project pursues the design of garments for ambulatory health monitoring that have the look and feel of every day clothing, together with an approach to monitoring that removes some of the barriers to patient compliance by automatically annotating physiological data with activities and motions, collecting data only during specific conditions, and having minimal impact on daily routine. The intellectual merits lie in the algorithms, design methodologies, and evaluation methodologies that enable wear-and-forget garments for ambulatory health monitoring. The approach developed by this project uses a computationally intensive pose estimation algorithm that automatically adapts a more computationally efficient algorithm for activity classification. This project addresses the challenges of providing garments that look and feel like everyday clothing by developing design and evaluation methodologies for incorporating fiber-based sensors into garments. These have significant advantages over discrete sensors by being woven or sewn into the fabric, covering much larger areas of a garment, and draping naturally. The broader impacts of the research lie in the potential to remove barriers that prevent the effective use of ambulatory health monitoring to improve the quality of life for patients and their families.

已经证明，在许多研究中，卧床健康监测可以为患者带来重大好处。 改善患者结果的最大希望在于长期对慢性病患者的卧床监测，以帮助医生和患者在危机阶段之前识别健康问题。 该项目追求服装的设计，以进行门诊健康监测，以每天服装的外观和感觉，以及一种监测方法，通过自动通过活动和动作自动注释生理数据，仅在特定条件下收集数据，并对日常例行造成最小的影响，从而消除患者合规性的某些障碍。 智力优点在于算法，设计方法和评估方法，这些方法可以使磨损服装用于门诊健康监测。 该项目开发的方法采用了一种计算密集型姿势估计算法，该算法会自动适应一种更有效的活动分类算法。 该项目解决了通过开发设计和评估方法，将基于纤维的传感器纳入服装的设计和评估方法，以提供看起来和感觉像日常服装的挑战。 通过编织或缝制在织物中，覆盖了更大的衣服区域并自然悬垂，这些优势比离散传感器具有显着优势。 这项研究的更广泛的影响在于消除障碍的潜力，以防止有效利用门诊健康监测以改善患者及其家人的生活质量。