Passive Activity Monitoring with Patient Identification and Gesture Detection

具有患者识别和手势检测功能的被动活动监控

• 批准号: 8463373
• 负责人: JAMES L WOLF
• 金额: $ 15.28万
• 依托单位: INGENIUM CARE, LLC
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-30 至 2013-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8463373
• 关键词: Activities of Daily Living; Algorithms; Alzheimer' s Disease; American; Area; Artificial Intelligence; Biological Sciences; Caring; Collection; Computer software; Computers; Data; Data Set; Decision Trees; Dementia; Detection; Development; Devices; Disabled Persons; Eating; Elderly; Ensure; Environment; Event; Facial Expression; Family Caregiver; Family member; Furniture; Gestures; Goals; Half-Life; Healthcare; Home environment; Hour; Human Resources; Independent Living; Individual; Interactive Communication; Laboratories; Learning; Life; Living Arrangement; Location; Marketing; Measures; Methods; Monitor; Motion; Nose; Outcome; Outcomes Research; Patients; Persons; Pharmaceutical Preparations; Post-Traumatic Stress Disorders; Process; Qualifying; Randomized; Reporting; Research; Running; Simulate; Soldier; Support System; System; Technology; Testing; Time; Touch sensation; Training; Work; base; care systems; cost; drinking; falls; forest; improved; instrument; monitoring device; new technology; older patient; phase 2 study; pill; point of care; sensor; software development; tool; volunteer

DESCRIPTION (provided by applicant): Elderly patients with Alzheimer's disease and dementia present a massive care challenge for family members and care professionals. In the last year of a patient's life, half of family caregivers report spending 46 or more hours a week assisting him/her with activities of daily living (ADL). Ingenium Care proposes to create a passive, self-learning, system for activity monitoring and support of elderly persons using the novel technology of Microsoft's Kinect device. This advanced activity monitoring combined with Ingenium Care's interactive communications and support system will extend independent living and the successful conduct of everyday tasks for the elderly with Alzheimer's disease, dementia, people with disabilities, and soldiers with PTSD and TBI. Existing monitoring technology has limited activity recognition capability or uses many sensors and wearable devices. The need for wearable devices requires cooperation from the elderly that may not reminder or resent to wear it. We propose to replace our existing wearable badge technology with a passive device based on the Kinect device from Microsoft. A network of these sensors provides precise location information within a home or facility and detects falls and gestures such as eating, drinking or taking medications. This device will eliminate the need to wear any device. Aim #1 - Goal: Develop Algorithms for Proof of Concept Gesture Recognition. Aim #2 - Goal: Do laboratory training and testing of detection algorithms utilizing a single work station. Aim #3 - Goal: Perform randomized activities and gestures in a simulated living environment and iteratively improve algorithms. PUBLIC HEALTH RELEVANCE: Narrative Today, 60 million Americans - one in five - require assistance in their living arrangements and daily activities. These are primarily elderly individuals with Alzheimer's disease, dementia, and also persons with disabilities. By applying the latest monitoring and artificial intelligence technologies, the outcomes of this research would enable the Ingenium Care system to improve the quality of home and institutional health care, and at the same time, reduce the cost of providing that care. The marketplace for technology to assist the elderly will grow sharply from $2 billion today to more than $20 billion by 2020, according to new reports from Frost and Sullivan and Forester Research (Liz Boehm, Principal Analyst for Healthcare and Life Sciences) entitled "Healthcare Unbound's Early Self-Pay Market".

描述（由申请人提供）：阿尔茨海默病和痴呆的老年患者对家庭成员和护理专业人员提出了巨大的护理挑战。在病人生命的最后一年，一半的家庭照顾者报告每周花费46小时或更多时间帮助他/她进行日常生活活动（ADL）。Ingenium Care建议使用微软Kinect设备的新技术创建一个被动、自学的活动监测和老年人支持系统。这种先进的活动监测与Ingenium Care的交互式通信和支持系统相结合，将延长老年痴呆症患者、老年痴呆症患者、残疾人以及患有创伤后应激障碍和创伤性脑损伤的士兵的独立生活和成功完成日常任务。现有的监测技术具有有限的活动识别能力或使用许多传感器和可穿戴设备。对可穿戴设备的需求需要老年人的合作，他们可能不会提醒或怨恨佩戴它。我们建议用基于微软Kinect设备的无源设备取代我们现有的可穿戴徽章技术。这些传感器的网络提供家庭或设施内的精确位置信息，并检测福尔斯和饮食或服药等手势。这种装置将消除佩戴任何装置的需要。目标#1 -目标：开发概念证明手势识别算法。目标#2 -目标：利用单个工作站进行实验室培训和检测算法测试。目标#3 -目标：在模拟的生活环境中执行随机活动和手势，并迭代改进算法。 公共卫生相关性：叙述今天，6000万美国人-五分之一-在他们的生活安排和日常活动中需要帮助。这些人主要是患有阿尔茨海默病、痴呆症的老年人，也有残疾人。通过应用最新的监测和人工智能技术，这项研究的成果将 使Ingenium Care系统能够提高家庭和机构医疗保健的质量，同时降低提供医疗保健的成本。帮助老年人的技术市场将从今天的20亿美元急剧增长到2020年的200多亿美元，根据Frost and Sullivan和Forester Research（医疗保健和生命科学首席分析师Liz Boehm）题为“医疗保健Unbound的早期自助支付市场”的新报告。