Multi-modal sensing for human activity recognition

Barbara Bruno, Jasmin Grosinger, F. Mastrogiovanni, F. Pecora, A. Saffiotti, Subhash Sathyakeerthy, A. Sgorbissa
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引用次数: 8

Abstract

Robots for the elderly are a particular category of home assistive robots, helping people in the execution of daily life tasks to extend their independent life. Such robots should be able to determine the level of independence of the user and track its evolution over time, to adapt the assistance to the person capabilities and needs. Human Activity Recognition systems employ various sensing strategies, relying on environmental or wearable sensors, to recognize the daily life activities which provide insights on the health status of a person. The main contribution of the article is the design of an heterogeneous information management framework, allowing for the description of a wide variety of human activities in terms of multi-modal environmental and wearable sensing data and providing accurate knowledge about the user activity to any assistive robot.
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人类活动识别的多模态传感
老年人机器人是家庭辅助机器人的一个特殊类别,帮助人们执行日常生活任务,延长他们的独立生活。这样的机器人应该能够确定用户的独立水平,并跟踪其随时间的演变,以适应人的能力和需求的援助。人类活动识别系统采用各种传感策略,依靠环境或可穿戴传感器来识别日常生活活动,从而提供对人的健康状况的见解。本文的主要贡献是设计了一个异构信息管理框架,允许在多模态环境和可穿戴传感数据方面描述各种各样的人类活动,并为任何辅助机器人提供有关用户活动的准确知识。
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