Evidence map›Paper›PMID 31340542›Full record

ArticleSensors (Basel, Switzerland)2019

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

Niccolò Mora, Ferdinando Grossi, Dario Russo, Paolo Barsocchi, Rui Hu, Thomas Brunschwiler, Bruno Michel, Francesca Cocchi, Enrico Montanari, Stefano Nunziata and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Niccolò MoraUniversità degli Studi di Parma, Dip. Ingegneria e Architettura, Parco Area delle Scienze 181/A, 43124 Parma (PR), Italy. niccolo.mora@unipr.it.ORCID 0000-0003-0093-0024
Ferdinando GrossiWiMonitor S.r.l, Via G. Tacchi 1, 38068 Rovereto (TN), Italy.ORCID 0000-0003-1693-0977
Dario RussoNational Research Council of Italy, Via Moruzzi 1, 56124 Pisa (PI), Italy.ORCID 0000-0003-3409-6189
Paolo BarsocchiNational Research Council of Italy, Via Moruzzi 1, 56124 Pisa (PI), Italy.ORCID 0000-0002-6862-7593
Rui HuIBM Research - Zurich, Saeumerstrasse 4, CH-8803 Rueschlikon, Switzerland.
Thomas BrunschwilerIBM Research - Zurich, Saeumerstrasse 4, CH-8803 Rueschlikon, Switzerland.
Bruno MichelIBM Research - Zurich, Saeumerstrasse 4, CH-8803 Rueschlikon, Switzerland.ORCID 0000-0002-1104-846X
Francesca CocchiAzienda Unita' Sanitaria Locale Di Parma, Str. Quartiere, 2/A, 43125 Parma (PR), Italy.
Enrico MontanariAzienda Unita' Sanitaria Locale Di Parma, Str. Quartiere, 2/A, 43125 Parma (PR), Italy.
Stefano NunziataLepida S.c.p.A, Via del Borgo di S. Pietro, 90/c, 40126 Bologna (BO), Italy.
Guido MatrellaUniversità degli Studi di Parma, Dip. Ingegneria e Architettura, Parco Area delle Scienze 181/A, 43124 Parma (PR), Italy.ORCID 0000-0002-0705-527X
Paolo CiampoliniUniversità degli Studi di Parma, Dip. Ingegneria e Architettura, Parco Area delle Scienze 181/A, 43124 Parma (PR), Italy.ORCID 0000-0001-8944-2152

Funding

Horizon 2020 732679
6 · The paper itself

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.

Indexed as

active assisted living (AAL)anomaly detectionbehavioural analysiscontinuous monitoringIoTsmart home

Identifiers

PMID31340542
PMCPMC6679511

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.