Vision-Based Evaluation of Mobility, Physical Health, and Rehabilitation Progress in Natural Settings

这项研究计划的高级目标是开发能够监测人类在自然环境中的运动和行动的计算机视觉工具和算法。这项研究的应用领域是评估老年人家中的行动能力、身体健康和康复进展。具体地说，我们将重点观察老年人在家中的动作、姿势和日常活动，以便自动和持续地评估他们的身体健康和行动能力。*医疗保健的进步和婴儿潮一代的老龄化导致**老年人口的规模和比例不断增加。促进和支持就地老龄化可以缓解这种人口结构变化带来的部分医疗压力。然而，如果没有适当的考虑，独居可能会给许多**老年人带来严重的健康和安全风险，特别是对那些患有慢性行动或认知障碍的人。*早期的研究表明，如果家庭视频监控技术允许参与者留在自己的家里，那么这种技术在老年人中是可以接受的。计算机视觉和机器学习的最新进展使得在自然环境中(即在家里)进行实时移动和身体健康监测成为可能，在提高老年人的生活质量方面具有很高的潜力，同时也提出了有趣和具有挑战性的计算机科学研究问题。*有兴趣更多了解这一研究项目的个人或公司，或有兴趣为其发展做出贡献或合作的个人或公司，请通过电子邮件taati@cs.utoronto.ca与首席研究员(B.Taati)联系。*

The high level objective of this program of research is to develop computer vision tools and algorithms capable of monitoring the movements and actions of humans in natural settings. The application area of this research is in the evaluation of mobility, physical health, and rehabilitation progress in the homes of older adults. Specifically, we will focus on observing the motion, pose, and daily activities of older adults in the home in order to automatically and continually assess their physical health and mobility.** **Advances in medical care and the aging of the baby boomer generation have resulted in the**increasing size and proportion of the older adult population. Promoting and supporting aging-in-**place alleviates some of the healthcare pressures resulting from this demographic change. Without**proper considerations, however, living alone could pose serious health and safety risks for many**older adults, particularly for those with chronic mobility or cognitive conditions.****Earlier research has shown the acceptability of home video monitoring technologies among older adults if the technology allowed the participants to remain in their own homes. Recent advances in computer vision and machine learning have made real-time mobility and physical health monitoring in natural settings, i.e., in the home, a within reach possibility with high potentials in improving the quality of life of older adults, while at the same time posing interesting and challenging computer science research questions. ****Individuals or companies interested in learning more about this program of research or interested in contributing or collaborating towards its development are encouraged to contact the principal investigator (B. Taati) via email at taati@cs.utoronto.ca.**********