Davidoff Hannah, Van den Bulcke Laura, Vandenbulcke Mathieu, De Vos Maarten, Van den Stock Jan, Van Helleputte Nick, Van Hoof Chris, Van Den Bossche Maarten J A
Department of Electrical Engineering (ESAT), KU Leuven, Heverlee, Belgium.
CSH (Circuits and Systems for Health) - imec, Heverlee, Belgium.
Innov Aging. 2022 Oct 15;6(7):igac064. doi: 10.1093/geroni/igac064. eCollection 2022.
Agitation, a critical behavioral and psychological symptom in dementia, has a profound impact on a patients' quality of life as well as their caregivers'. Autonomous and objective characterization of agitation with multimodal systems has the potential to capture key patient responses or agitation triggers.
In this article, we describe our multimodal system design that encompasses contextual parameters, physiological parameters, and psychological parameters. This design is the first to include all three of these facets in an > 1 study. Using a combination of fixed and wearable sensors and a custom-made app for psychological annotation, we aim to identify physiological markers and contextual triggers of agitation.
A discussion of both the clinical as well as the technical implementation of the to-date data collection protocol is presented, as well as initial insights into pilot study data collection.
The ongoing data collection moves us toward improved agitation quantification and subsequent prediction, eventually enabling just-in-time intervention.
激越作为痴呆症中一种关键的行为和心理症状，对患者及其照料者的生活质量都有深远影响。利用多模态系统对激越进行自主且客观的特征描述，有可能捕捉到患者的关键反应或激越触发因素。
在本文中，我们描述了我们的多模态系统设计，该设计涵盖情境参数、生理参数和心理参数。此设计是首个在一项研究中包含所有这三个方面的设计。通过结合固定传感器和可穿戴传感器以及一款用于心理标注的定制应用程序，我们旨在识别激越的生理标志物和情境触发因素。
本文介绍了迄今为止数据收集方案的临床及技术实施情况，以及对试点研究数据收集的初步见解。
正在进行的数据收集使我们朝着改进激越量化及后续预测的方向迈进，最终实现及时干预。
