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基于物联网的家庭监测:通过行为分析支持从业者评估

IoT-Based Home Monitoring: Supporting Practitioners' Assessment by Behavioral Analysis.

作者信息

Mora Niccolò, Grossi Ferdinando, Russo Dario, Barsocchi Paolo, Hu Rui, Brunschwiler Thomas, Michel Bruno, Cocchi Francesca, Montanari Enrico, Nunziata Stefano, Matrella Guido, Ciampolini Paolo

机构信息

Università degli Studi di Parma, Dip. Ingegneria e Architettura, Parco Area delle Scienze 181/A, 43124 Parma (PR), Italy.

WiMonitor S.r.l, Via G. Tacchi 1, 38068 Rovereto (TN), Italy.

出版信息

Sensors (Basel). 2019 Jul 23;19(14):3238. doi: 10.3390/s19143238.

DOI:10.3390/s19143238
PMID:31340542
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6679511/
Abstract

This paper introduces technical solutions devised to support the Deployment Site - Regione Emilia Romagna (DS-RER) of the ACTIVAGE project. The ACTIVAGE project aims at promoting IoT (Internet of Things)-based solutions for Active and Healthy ageing. DS-RER focuses on improving continuity of care for older adults (65+) suffering from aftereffects of a stroke event. A Wireless Sensor Kit based on Wi-Fi connectivity was suitably engineered and realized to monitor behavioral aspects, possibly relevant to health and wellbeing assessment. This includes bed/rests patterns, toilet usage, room presence and many others. Besides hardware design and validation, cloud-based analytics services are introduced, suitable for automatic extraction of relevant information (trends and anomalies) from raw sensor data streams. The approach is general and applicable to a wider range of use cases; however, for readability's sake, two simple cases are analyzed, related to bed and toilet usage patterns. In particular, a regression framework is introduced, suitable for detecting trends (long and short-term) and labeling anomalies. A methodology for assessing multi-modal daily behavioral profiles is introduced, based on unsupervised clustering techniques. The proposed framework has been successfully deployed at several real-users' homes, allowing for its functional validation. Clinical effectiveness will be assessed instead through a Randomized Control Trial study, currently being carried out.

摘要

本文介绍了为支持ACTIVAGE项目的部署站点——艾米利亚-罗马涅大区(DS-RER)而设计的技术解决方案。ACTIVAGE项目旨在推广基于物联网(IoT)的积极健康老龄化解决方案。DS-RER专注于改善对中风后遗症老年患者(65岁以上)的持续护理。基于Wi-Fi连接的无线传感器套件经过精心设计和实现,用于监测可能与健康和福祉评估相关的行为方面。这包括卧床/休息模式、厕所使用情况、房间停留情况等。除了硬件设计和验证,还引入了基于云的分析服务,适用于从原始传感器数据流中自动提取相关信息(趋势和异常)。该方法具有通用性,适用于更广泛的用例;然而,为了便于阅读,分析了两个简单的案例,与卧床和厕所使用模式相关。特别是,引入了一个回归框架,适用于检测趋势(长期和短期)并标记异常。介绍了一种基于无监督聚类技术评估多模式日常行为概况的方法。所提出的框架已成功部署在多个真实用户家中,从而实现了其功能验证。相反,临床有效性将通过目前正在进行的随机对照试验研究来评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/f32718be7b08/sensors-19-03238-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/057026a02276/sensors-19-03238-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/d34211388589/sensors-19-03238-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/c7d5f2d4fc94/sensors-19-03238-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/5e35ce311cdf/sensors-19-03238-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/f32718be7b08/sensors-19-03238-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/057026a02276/sensors-19-03238-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/d34211388589/sensors-19-03238-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/c7d5f2d4fc94/sensors-19-03238-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/5e35ce311cdf/sensors-19-03238-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f108/6679511/f32718be7b08/sensors-19-03238-g005.jpg

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