Evidence map›Paper›PMID 37274667›Full record

ArticleHeliyon2023

Mobile and wearable technologies for the analysis of Ten Meter Walk Test: A concise systematic review.

Cristiana Lopes Gabriel, Ivan Miguel Pires, Paulo Jorge Coelho, Eftim Zdravevski, Petre Lameski, Hiren Mewada, Filipe Madeira, Nuno M Garcia, Carlos Carreto

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. 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
1.4field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  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

9 authors at 6 institutions in 3 countries.

Cristiana Lopes GabrielResearch Unit for Inland Development, Polytechnic of Guarda, Guarda, Portugal.
Ivan Miguel PiresInstituto de Telecomunicações, 6201-001 Covilhã, Portugal.
Paulo Jorge CoelhoPolytechnic of Leiria, Leiria, Portugal.
Eftim ZdravevskiFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000, Skopje, Macedonia.
Petre LameskiFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000, Skopje, Macedonia.
Hiren MewadaDepartment of Electrical Engineering, Prince Mohammad Bin Fahd University, Al Khobar, 31952, Kingdom of Saudi Arabia.
Filipe MadeiraDepartment of Informatics and Quantitative Methods, Research Centre for Arts and Communication (CIAC)/Pole of Digital Literacy and Social Inclusion, Polytechnic Institute of Santarém, 2001-904 , Santarém, Portugal.
Nuno M GarciaInstituto de Telecomunicações, 6201-001 Covilhã, Portugal.
Carlos CarretoResearch Unit for Inland Development, Polytechnic of Guarda, Guarda, Portugal.
Instituto Politécnico da Guarda · PTInstituto Politécnico de Santarém · PTSs. Cyril and Methodius University in Skopje · MKInstituto Politécnico de Leiria · PTPrince Mohammad bin Fahd University · SAUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physical issues started to receive more attention due to the sedentary lifestyle prevalent in modern culture. The Ten Meter Walk Test allows measuring the person's capacity to walk along 10 m and analyzing the advancement of various medical procedures for ailments, including stroke. This systematic review is related to the use of mobile or wearable devices to measure physical parameters while administering the Ten Meter Walk Test for the analysis of the performance of the test. We applied the PRISMA methodology for searching the papers related to the Ten Meter Walk Test. Natural Language Processing (NLP) algorithms were used to automate the screening process. Various papers published in two decades from multiple scientific databases, including IEEE Xplore, Elsevier, Springer, EMBASE, SCOPUS, Multidisciplinary Digital Publishing Institute (MDPI), and PubMed Central were analyzed, focusing on various diseases, devices, features, and methods. The study reveals that chronometer and accelerometer sensors measuring spatiotemporal features are the most pertinent in the Gait characterization of most diseases. Likewise, all studies emphasized the close relation between the quality of the sensor's data obtained and the system's ultimate accuracy. In other words, calibration procedures are needed because of the body part where the sensor is worn and the type of sensor. In addition, using ambient sensors providing kinematic and kinetic features in conjunction with wearable sensors and consistently acquiring walking signals can enhance the system's performance. The most common weaknesses in the analyzed studies are the sample size and the unavailability of continuous monitoring devices for measuring the Ten Meter Walk Test.

Indexed as

Mobile devicesSensorsSystematic reviewTelemedicineTen meter Walk testWearable devices

Identifiers

PMID37274667
PMCPMC10238910
OpenAlexW4378071479

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.