Evidence map›Paper›PMID 31065258›Full record

ArticleComputational intelligence and neuroscience2019

Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot.

Francisco Gomez-Donoso, Félix Escalona, Francisco Miguel Rivas, Jose Maria Cañas, Miguel Cazorla

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Francisco Gomez-DonosoInstitute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, Spain.ORCID 0000-0002-7830-2661
Félix EscalonaInstitute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, Spain.ORCID 0000-0003-2245-601X
Francisco Miguel RivasRoboticsLab-URJC, Universidad Rey Juan Carlos, Madrid, Spain.
Jose Maria CañasRoboticsLab-URJC, Universidad Rey Juan Carlos, Madrid, Spain.ORCID 0000-0003-4179-2211
Miguel CazorlaInstitute for Computer Research, University of Alicante, P.O. Box 99, 03080 Alicante, Spain.ORCID 0000-0001-6805-3633

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ambient assisted living (AAL) environments are currently a key focus of interest as an option to assist and monitor disabled and elderly people. These systems can improve their quality of life and personal autonomy by detecting events such as entering potentially dangerous areas, potential fall events, or extended stays in the same place. Nonetheless, there are areas that remain outside the scope of AAL systems due to the placement of cameras. There also exist sources of danger in the scope of the camera that the AAL system cannot detect. These sources of danger are relatively small in size, occluded, or nonstatic. To solve this problem, we propose the inclusion of a robot which maps such uncovered areas looking for new potentially dangerous areas that go unnoticed by the AAL. The robot then sends this information to the AAL system in order to improve its performance. Experimentation in real-life scenarios successfully validates our approach.

Indexed as

AlgorithmsDelivery of Health CareQuality of LifeRoboticsAgingHumansRisk

Identifiers

PMID31065258
PMCPMC6466947

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.