Eating activity primitives detection - a step towards ADL recognition

A. Tolstikov, J. Biswas, C. Tham, P. Yap
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引用次数: 38

Abstract

Activity of daily living (ADL) monitoring is important in order to determine the well being of elderly persons in their home settings. One important question is, ldquoIs the elderly person able to eat properly on his own?rdquo In this paper we present some results of our preliminary work on an algorithm for detection of the eating activity. The algorithm uses a dynamic Bayesian network based approach to reduce the complexity of determining states. Initial results are quite promising and point to a general algorithmic approach that a) uses multiple modalities of sensors for gathering data, b) detects activity primitives and c) stores detected activity primitives as micro-context for future use.
进食活动原语检测——迈向ADL识别的一步
日常生活活动(ADL)监测对于确定老年人在其家庭环境中的健康状况非常重要。一个重要的问题是,老人是否能够自己正常饮食?在本文中,我们介绍了一些初步工作的结果,用于检测进食活动的算法。该算法采用基于动态贝叶斯网络的方法来降低状态确定的复杂性。初步结果非常有希望,并指出了一种通用算法方法:a)使用多种传感器模式来收集数据,b)检测活动原语,c)将检测到的活动原语存储为微上下文以供将来使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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