Passive Activity Monitoring with Patient Identification and Gesture Detection

描述（由申请人提供）：老年阿尔茨海默病和痴呆症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，一半的家庭护理人员报告每周花费46小时或更多时间帮助他/她进行日常生活活动（ADL）。Ingenium Care计划使用微软Kinect设备的新技术，创建一个被动的、自我学习的活动监测系统，并为老年人提供支持。这种先进的活动监测与Ingenium Care的互动通信和支持系统相结合，将为患有阿尔茨海默病、痴呆症的老年人、残疾人以及患有创伤后应激障碍和创伤性脑损伤的士兵延长独立生活和成功执行日常任务。现有的监测技术活动识别能力有限，或者使用了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配合，他们可能不会提醒或反对佩戴它。我们建议用基于微软Kinect设备的被动设备取代我们现有的可穿戴徽章技术。这些传感器组成的网络可以在家中或设施内提供精确的位置信息，并检测跌倒和吃、喝或服药等手势。该设备将消除佩戴任何设备的需要。目标1：开发用于概念手势识别的算法。目标2：利用单个工作站进行检测算法的实验室培训和测试。目标3：在模拟生活环境中执行随机活动和手势，并迭代改进算法。

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".