文章基本信息

标题：Recognition of Physical Activities from a Single Arm-Worn Accelerometer: A Multiway Approach
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作者：Lieven Billiet ; Thijs Swinnen ; Kurt de Vlam 等
期刊名称：Informatics
电子版ISSN：2227-9709
出版年度：2018
卷号：5
期号：2
页码：20
DOI：10.3390/informatics5020020
语种：English
出版社：MDPI Publishing
摘要：In current clinical practice, functional limitations due to chronic musculoskeletal diseases are still being assessed subjectively, e.g., using questionnaires and function scores. Performance-based methods, on the other hand, offer objective insights. Hence, they recently attracted more interest as an additional source of information. This work offers a step towards the shift to performance-based methods by recognizing standardized activities from continuous readings using a single accelerometer mounted on a patient’s arm. The proposed procedure consists of two steps. Firstly, activities are segmented, including rejection of non-informative segments. Secondly, the segments are associated to predefined activities using a multiway pattern matching approach based on higher order discriminant analysis (HODA). The two steps are combined into a multi-layered framework. Experiments on data recorded from 39 patients with spondyloarthritis show results with a classification accuracy of 94.34% when perfect segmentation is assumed. Automatic segmentation has 89.32% overlap with this ideal scenario. However, combining both drops performance to 62.34% due to several badly-recognized subjects. Still, these results are shown to significantly outperform a more traditional pattern matching approach. Overall, the work indicates promising viability of the technique to automate recognition and, through future work, assessment, of functional capacity.
关键词：physical therapy; activity recognition; accelerometry; tensor decomposition; classification with rejection physical therapy ; activity recognition ; accelerometry ; tensor decomposition ; classification with rejection