Evidence map›Paper›PMID 38297359›Full record

ArticleBiomedical engineering online2024

Beyond timing and step counting in 360° turning-in-place assessment: a scoping review.

Slavka Netukova, Lucie Horakova, Zoltan Szabo, Radim Krupicka

Open access · goldAbstract readScoping Review
In one paragraph

Article in Biomedical engineering online, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.4field-weighted citation impact, top 8% of its field
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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Turning as a single and dual task-associations with Alzheimer's and vascular pathologies in cognitively healthy older people.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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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

4 authors at 1 institution in 1 country.

Slavka NetukovaFaculty of Biomedical Engineering, Department of Biomedical Informatics, Czech Technical University, Nam Sitna 3105, Prague, Czech Republic. slavka.netukova@fbmi.cvut.cz.
Lucie HorakovaFaculty of Biomedical Engineering, Department of Biomedical Informatics, Czech Technical University, Nam Sitna 3105, Prague, Czech Republic.
Zoltan SzaboFaculty of Biomedical Engineering, Department of Biomedical Informatics, Czech Technical University, Nam Sitna 3105, Prague, Czech Republic.
Radim KrupickaFaculty of Biomedical Engineering, Department of Biomedical Informatics, Czech Technical University, Nam Sitna 3105, Prague, Czech Republic.
Czech Technical University in Prague · CZ

Funding

Ministerstvo Školství, Mládeže a Tělovýchovy LX22NPO5107Ministerstvo Zdravotnictví Ceské Republiky NU20-04-00327
6 · The paper itself

Abstract

backgroundTurning in place is a challenging motor task and is used as a brief assessment test of lower limb function and dynamic balance. This review aims to examine how research of instrumented analysis of turning in place is implemented. In addition to reporting the studied population, we covered acquisition systems, turn detection methods, quantitative parameters, and how these parameters are computed.

methodsFollowing the development of a rigorous search strategy, the Web of Science and Scopus were systematically searched for studies involving the use of turning-in-place. From the selected articles, the study population, types of instruments used, turn detection method, and how the turning-in-place characteristics were calculated.

resultsTwenty-one papers met the inclusion criteria. The subject groups involved in the reviewed studies included young, middle-aged, and older adults, stroke, multiple sclerosis and Parkinson's disease patients. Inertial measurement units (16 studies) and motion camera systems (5 studies) were employed for gathering measurement data, force platforms were rarely used (2 studies). Two studies used commercial software for turn detection, six studies referenced previously published algorithms, two studies developed a custom detector, and eight studies did not provide any details about the turn detection method. The most frequently used parameters were mean angular velocity (14 cases, 7 studies), turn duration (13 cases, 13 studies), peak angular velocity (8 cases, 8 studies), jerkiness (6 cases, 5 studies) and freezing-of-gait ratios (5 cases, 5 studies). Angular velocities were derived from sensors placed on the lower back (7 cases, 4 studies), trunk (4 cases, 2 studies), and shank (2 cases, 1 study). The rest (9 cases, 8 studies) did not report sensor placement. Calculation of the freezing-of-gait ratio was based on the acceleration of the lower limbs in all cases. Jerkiness computation employed acceleration in the medio-lateral (4 cases) and antero-posterior (1 case) direction. One study did not reported any details about jerkiness computation.

conclusionThis review identified the capabilities of turning-in-place assessment in identifying movement differences between the various subject groups. The results, based on data acquired by inertial measurement units across studies, are comparable. A more in-depth analysis of tests developed for gait, which has been adopted in turning-in-place, is needed to examine their validity and accuracy.

Indexed as

Parkinson DiseaseStrokeAgedGaitHumansLegMiddle AgedMovementBalanceCamera systemInertial measurement unitWearable sensor

Identifiers

PMID38297359
PMCPMC10832107
OpenAlexW4391383178

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.