Evidence map›Paper›PMID 34640745›Full record

ArticleSensors (Basel, Switzerland)2021

Real-Time Back Surface Landmark Determination Using a Time-of-Flight Camera.

Daniel Ledwoń, Marta Danch-Wierzchowska, Marcin Bugdol, Karol Bibrowicz, Tomasz Szurmik, Andrzej Myśliwiec, Andrzej W Mitas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

7 authors.

Daniel LedwońFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, Poland.ORCID 0000-0001-7704-2901
Marta Danch-WierzchowskaFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, Poland.ORCID 0000-0002-5912-2753
Marcin BugdolFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, Poland.ORCID 0000-0003-4585-1733
Karol BibrowiczScience and Research Center of Body Posture, College of Education and Therapy in Poznań, 61-473 Poznań, Poland.ORCID 0000-0002-1422-3606
Tomasz SzurmikFaculty of Arts and Educational Science, University of Silesia, 43-400 Cieszyn, Poland.ORCID 0000-0001-5085-0976
Andrzej MyśliwiecLaboratory of Physiotherapy and Physioprevention, Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, 40-065 Katowice, Poland.ORCID 0000-0003-2183-1156
Andrzej W MitasFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, Poland.ORCID 0000-0001-7833-5845

Funding

Polish Ministry of Science and Silesian University of Technology 07/010/BK_21/1006 (BK-296/RIB1/2021)
6 · The paper itself

Abstract

Postural disorders, their prevention, and therapies are still growing modern problems. The currently used diagnostic methods are questionable due to the exposure to side effects (radiological methods) as well as being time-consuming and subjective (manual methods). Although the computer-aided diagnosis of posture disorders is well developed, there is still the need to improve existing solutions, search for new measurement methods, and create new algorithms for data processing. Based on point clouds from a Time-of-Flight camera, the presented method allows a non-contact, real-time detection of anatomical landmarks on the subject's back and, thus, an objective determination of trunk surface metrics. Based on a comparison of the obtained results with the evaluation of three independent experts, the accuracy of the obtained results was confirmed. The average distance between the expert indications and method results for all landmarks was 27.73 mm. A direct comparison showed that the compared differences were statically significantly different; however, the effect was negligible. Compared with other automatic anatomical landmark detection methods, ours has a similar accuracy with the possibility of real-time analysis. The advantages of the presented method are non-invasiveness, non-contact, and the possibility of continuous observation, also during exercise. The proposed solution is another step in the general trend of objectivization in physiotherapeutic diagnostics.

Indexed as

Models, AnatomicPostureAlgorithmsBackBiomechanical Phenomenaanatomical landmarksphysiotherapypoint cloudreal-time detectiontrunk surface metrics

Identifiers

PMID34640745
PMCPMC8512900

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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.