使用移动辅助工具的老年人灵活活动跟踪-自动识别运动模式的探索性研究

Dimitri Vargemidis, K. Gerling, L. Geurts, V. Abeele
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引用次数: 0

摘要

使用助行器(如助行器、轮椅)的老年人无法使用可穿戴活动追踪器,因为此类运动模式(mm)的追踪器的准确性大大下降。作为解决这个问题的第一步,我们实现并测试了一个最小距离分类器,以自动识别七种模式中使用的MM,包括有或没有移动辅助,以及没有移动。根据测试设置,我们的分类器达到了82%到100%之间的准确率。这些发现可以在未来的工作中加以利用,将分类器与针对每种移动辅助设备量身定制的算法结合起来,使行动不便的用户也可以使用活动跟踪器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Activity Tracking for Older Adults Using Mobility Aids — An Exploratory Study on Automatically Identifying Movement Modality
Wearable activity trackers are inaccessible to older adults who use mobility aids (e.g., walker, wheelchair), because the accuracy of trackers drops considerably for such movement modalities (MMs). As an initial step to address this problem, we implemented and tested a minimum distance classifier to automatically identify the used MM out of seven modalities, including movement with or without a mobility aid, and no movement. Depending on the test setup, our classifier achieves accuracies between 82 % and 100 %. These findings can be leveraged in future work to combine the classifier with algorithms tailored to each mobility aid to make activity trackers accessible to users with limited mobility.
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