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

这个研究项目的高水平目标是开发计算机视觉工具和算法，能够监测人类在自然环境中的运动和行为。本研究的应用领域是对老年人家庭活动能力、身体健康和康复进展的评估。具体来说，我们将专注于观察老年人在家中的运动、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活动能力。** **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“就地养老”可减轻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，尤其是那些有慢性行动不便或认知障碍的老年人。****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中，那么老年人可以接受该技术。计算机视觉和机器学习的最新进展使得在自然环境中（即在家中）实时移动和身体健康监测成为一种触手可及的可能性，在改善老年人的生活质量方面具有很高的潜力，同时提出了有趣和具有挑战性的计算机科学研究问题。****有兴趣了解更多关于这个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，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.**********