SGER: Assisted Cognition: First Steps Towards Computer Aids for People with Alzheimer's Disease

SGER：辅助认知：为阿尔茨海默病患者提供计算机辅助的第一步

• 批准号: 0225774
• 负责人: Oren Etzioni
• 金额: $ 9.95万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0225774&HistoricalAwards=false
• 关键词: SGER; Assisted; Cognition; First; Steps

This small grant for exploratory research will support development of novel computer systems that will enhance the quality of life of people suffering from Alzheimer's Disease and similar cognitive disorders. Assisted Cognition systems use ubiquitous computing and artificial intelligence technology to replace some of the memory and problem-solving abilities that have been lost by an Alzheimer's patient. Assisted Cognition systems: sense aspects of an individual's location and environment, both outdoors and at home, relying on a wide range of sensors such as Global Positioning Systems (GPS), active badges, motion detectors, and other ubiquitous computing infrastructure; learn to interpret patterns of everyday behavior, and recognize signs of distress, disorientation, or confusion, using techniques from state estimation, plan recognition, and machine learning; offer help to patients through various kinds of interventions including speech and natural language processing; and alert human care-givers in case of danger.Two concrete examples of the Assisted Cognition systems that will be developed are an activity compass that helps reduce spatial disorientation both inside and outside the home, and an adaptive prompter that helps patients carry out multi-step everyday tasks. This project will explore an emerging area that could be of great humanitarian, commercial, social, and scientific importance in the coming decades.

这笔用于探索性研究的小额赠款将支持开发新的计算机系统，以提高阿尔茨海默病和类似认知障碍患者的生活质量。辅助认知系统使用无处不在的计算和人工智能技术来取代阿尔茨海默氏症患者失去的一些记忆和解决问题的能力。辅助认知系统：感知个人的位置和环境的各个方面，包括户外和家中，依赖于广泛的传感器，如全球定位系统（GPS），活动徽章，运动探测器和其他无处不在的计算基础设施;学习解释日常行为模式，并使用状态估计，计划识别和机器学习的技术识别痛苦，迷失方向或混乱的迹象;通过包括语音和自然语言处理在内的各种干预措施为患者提供帮助;并在危险情况下提醒人类护理人员。将开发的辅助认知系统的两个具体例子是有助于减少家庭内外空间定向障碍的活动指南针，以及帮助患者执行多步骤日常任务的自适应导航仪。该项目将探索一个在未来几十年可能具有重大人道主义，商业，社会和科学重要性的新兴领域。