Evidence map›Paper›PMID 34127879›Full record

ArticleJournal of intelligent information systems2021

Smart integration of sensors, computer vision and knowledge representation for intelligent monitoring and verbal human-computer interaction.

Thanassis Mavropoulos, Spyridon Symeonidis, Athina Tsanousa, Panagiotis Giannakeris, Maria Rousi, Eleni Kamateri, Georgios Meditskos, Konstantinos Ioannidis, Stefanos Vrochidis, Ioannis Kompatsiaris

Abstract read
In one paragraph

Article in Journal of intelligent information systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Thanassis MavropoulosCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.ORCID 0000-0002-7326-5910
Spyridon SymeonidisCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Athina TsanousaCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Panagiotis GiannakerisCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Maria RousiCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Eleni KamateriCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Georgios MeditskosCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Konstantinos IoannidisCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Stefanos VrochidisCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.
Ioannis KompatsiarisCentre for Research and Technology-Hellas, Information Technologies Institute, GR 57001 Thermi, Thessaloniki Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The details presented in this article revolve around a sophisticated monitoring framework equipped with knowledge representation and computer vision capabilities, that aims to provide innovative solutions and support services in the healthcare sector, with a focus on clinical and non-clinical rehabilitation and care environments for people with mobility problems. In contemporary pervasive systems most modern virtual agents have specific reactions when interacting with humans and usually lack extended dialogue and cognitive competences. The presented tool aims to provide natural human-computer multi-modal interaction via exploitation of state-of-the-art technologies in computer vision, speech recognition and synthesis, knowledge representation, sensor data analysis, and by leveraging prior clinical knowledge and patient history through an intelligent, ontology-driven, dialogue manager with reasoning capabilities, which can also access a web search and retrieval engine module. The framework's main contribution lies in its versatility to combine different technologies, while its inherent capability to monitor patient behaviour allows doctors and caregivers to spend less time collecting patient-related information and focus on healthcare. Moreover, by capitalising on voice, sensor and camera data, it may bolster patients' confidence levels and encourage them to naturally interact with the virtual agent, drastically improving their moral during a recuperation process.

Indexed as

Computer visionHealthcareHuman-computer interactionNatural language processingPervasive systemsSensors

Identifiers

PMID34127879
PMCPMC8190522

What OpenQuestion holds

Textmetadata
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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.