Evidence map›Paper›PMID 35214508›Full record

ArticleSensors (Basel, Switzerland)2022

Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System.

Barbara Pȩkala, Teresa Mroczek, Dorota Gil, Michal Kepski

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Intelligent Sensors for Human Motion Analysis.Sensors (Basel, Switzerland) · 2022
    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

4 authors.

Barbara PȩkalaInstitute of Computer Science, University of Rzeszów, 35-310 Rzeszów, Poland.ORCID 0000-0002-5501-5467
Teresa MroczekDepartment of Artificial Intelligence, University of Information Technology and Management, 35-225 Rzeszów, Poland.ORCID 0000-0002-6064-9528
Dorota GilDepartment of Artificial Intelligence, University of Information Technology and Management, 35-225 Rzeszów, Poland.ORCID 0000-0001-6663-7571
Michal KepskiInstitute of Computer Science, University of Rzeszów, 35-310 Rzeszów, Poland.ORCID 0000-0003-1225-9143

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture detection problem, which is a part of fall detection system. Fall detection, using depth maps obtained by the Microsoft Kinect sensor, is a two-stage method. We concentrate on the first stage of the system, that is, pose recognition from a depth map. For lying pose detection, a new hybrid FRSystem is proposed. In the system, two rule sets are investigated, the first one created based on a domain knowledge and the second induced based on the rough set theory. Additionally, two inference aggregation approaches are considered with and without the knowledge measure. The results indicate that the new axiomatic definition of knowledge measures, which we propose has a positive impact on the effectiveness of inference and the rule induction method reducing the number of rules in a set maintains it.

Indexed as

Accidental FallsFuzzy LogicAlgorithmsHumansPostureRecognition, Psychologyaggregation functionfuzzy inferenceknowledge measureposture detectionprecedence indicatorrule induction

Identifiers

PMID35214508
PMCPMC8877837

What OpenQuestion holds

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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.