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

Articolo
Data di Pubblicazione:
2019
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.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
IoT; smart home; behavioural analysis; active assisted living (AAL); anomaly detection; continuous monitoring
Elenco autori:
Barsocchi, Paolo; Russo, Dario
Autori di Ateneo:
BARSOCCHI PAOLO
RUSSO DARIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/391045
Link al Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/391045/119503/prod_405018-doc_141448.pdf
Pubblicato in:
SENSORS (BASEL)
Journal
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URL

https://www.mdpi.com/1424-8220/19/14/3238
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