On the applicability of clinical observation tools for human activity annotation

2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) Pub Date : 2017-03-13 DOI:10.1109/PERCOMW.2017.7917545

Frank Krüger, Christina Heine, Sebastian Bader, Albert Hein, S. Teipel, T. Kirste

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引用次数: 9

Abstract

The annotation of human activity is a crucial prerequisite for applying methods of supervised machine learning. It is typically either obtained by live annotation by the participant or by video log analysis afterwards. Both methods, however, suffer from disadvantages when applied in dementia related nursing homes. On the one hand, people suffering from dementia are not able to produce such annotation and on the other hand, video observation requires high technical effort. The research domain of quality of care addresses these issues by providing observation tools that allow the simultaneous live observation of up to eight participants - dementia care mapping (DCM). We developed an annotation scheme based on the popular clinical observation tool DCM to obtain annotation about challenging behaviours. In this paper, we report our experiences with this approach and discuss the applicability of clinical observation tools in the domain of automatic human activity assessment.

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论临床观察工具在人体活动注释中的适用性

人类活动的注释是应用监督式机器学习方法的关键先决条件。它通常通过参与者的实时注释或随后的视频日志分析获得。但是，这两种方法在痴呆症相关的养老院中都有缺点。一方面，患有痴呆症的人无法产生这样的注释，另一方面，视频观察需要很高的技术努力。护理质量的研究领域通过提供观察工具来解决这些问题，这些工具允许同时对多达8名参与者进行现场观察-痴呆症护理绘图(DCM)。我们开发了一种基于流行的临床观察工具DCM的注释方案，以获得对挑战行为的注释。在本文中，我们报告了我们使用这种方法的经验，并讨论了临床观察工具在人类活动自动评估领域的适用性。

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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2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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