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可穿戴技术在痴呆症患者重要时刻检测中的应用。

Wearable Technology for Detecting Significant Moments in Individuals with Dementia.

机构信息

Biosignal Interaction and Personhood Technology Lab, McGill University, Montreal, Quebec H3G 1A4, Canada.

School of Physical and Occupational Therapy, McGill University, Montreal, Quebec H3G 1Y5, Canada.

出版信息

Biomed Res Int. 2019 Sep 25;2019:6515813. doi: 10.1155/2019/6515813. eCollection 2019.

DOI:10.1155/2019/6515813
PMID:31662986
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6778872/
Abstract

The detection of significant moments can support the care of individuals with dementia by making visible what is most meaningful to them and maintaining a sense of interpersonal connection. We present a novel intelligent assistive technology (IAT) for the detection of significant moments based on patterns of physiological signal changes in individuals with dementia and their caregivers. The parameters of the IAT are tailored to each individual's idiosyncratic physiological response patterns through an iterative process of incorporating subjective feedback on videos extracted from candidate significant moments identified through the IAT algorithm. The IAT was tested on three dyads (individual with dementia and their primary caregiver) during an eight-week movement program. Upon completion of the program, the IAT identified distinct, personal characteristics of physiological responsiveness in each participant. Tailored algorithms could detect moments of significance experienced by either member of the dyad with an agreement with subjective reports of 70%. These moments were constituted by both physical and emotional significances (e.g., experiences of pain or anxiety) and interpersonal significance (e.g., moments of heighted connection). We provide a freely available MATLAB toolbox with the IAT software in hopes that the assistive technology community can benefit from and contribute to these tools for understanding the subjective experiences of individuals with dementia.

摘要

重要时刻的检测可以通过展示对痴呆症患者最有意义的事物并保持人际联系感,来支持他们的护理。我们提出了一种新颖的基于痴呆症患者及其护理人员生理信号变化模式的智能辅助技术 (IAT) 来检测重要时刻。通过将主观反馈纳入通过 IAT 算法识别的候选重要时刻的视频中,该 IAT 通过迭代过程针对每个人的独特生理反应模式定制参数。IAT 在三个二人组(痴呆症患者及其主要照顾者)中进行了为期八周的运动计划的测试。在计划完成后,IAT 确定了每个参与者的生理反应的独特个人特征。定制算法可以以 70%的主观报告一致性检测到二人组中任意成员的重要时刻。这些时刻包括身体和情感意义(例如,疼痛或焦虑的体验)以及人际意义(例如,连接感增强的时刻)。我们提供了一个带有 IAT 软件的免费 MATLAB 工具箱,希望辅助技术社区能够从这些工具中受益,并为理解痴呆症患者的主观体验做出贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/88395dc4bbcb/BMRI2019-6515813.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/c690b35a6c1b/BMRI2019-6515813.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/54dbf6bf4268/BMRI2019-6515813.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/7e4720f805f5/BMRI2019-6515813.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/897c5d247b31/BMRI2019-6515813.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/88395dc4bbcb/BMRI2019-6515813.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/c690b35a6c1b/BMRI2019-6515813.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/54dbf6bf4268/BMRI2019-6515813.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/7e4720f805f5/BMRI2019-6515813.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/897c5d247b31/BMRI2019-6515813.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1794/6778872/88395dc4bbcb/BMRI2019-6515813.005.jpg

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