Evidence map›Paper›PMID 36862498›Full record

ArticleJMIR rehabilitation and assistive technologies2023

Smartphone Global Positioning System-Based System to Assess Mobility in Health Research: Development, Accuracy, and Usability Study.

Robert P Spang, Christine Haeger, Sandra A Mümken, Max Brauer, Jan-Niklas Voigt-Antons, Paul Gellert

Open access · goldFull text read
In one paragraph

Article in JMIR rehabilitation and assistive technologies, 2023. 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
0.3field-weighted citation impact, top 28% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Trial
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

6 authors at 3 institutions in 1 country.

Robert P SpangQuality and Usability Lab, Technische Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0001-6580-9060
Christine HaegerInstitute of Medical Sociology and Rehabilitation Science - Charité, Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-5631-838X
Sandra A MümkenInstitute of Medical Sociology and Rehabilitation Science - Charité, Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-0603-0855
Max BrauerQuality and Usability Lab, Technische Universität Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0002-2073-4445
Jan-Niklas Voigt-AntonsImmersive Reality Lab, University of Applied Sciences Hamm-Lippstadt, Lippstadt, Germany.ORCID https://orcid.org/0000-0002-2786-9262
Paul GellertInstitute of Medical Sociology and Rehabilitation Science - Charité, Universitätsmedizin Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0001-7492-7210
Charité - Universitätsmedizin Berlin · DETechnische Universität Berlin · DEGerman Research Centre for Artificial Intelligence · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs global positioning system (GPS) measurement is getting more precise and affordable, health researchers can now objectively measure mobility using GPS sensors. Available systems, however, often lack data security and means of adaptation and often rely on a permanent internet connection.

objectiveTo overcome these issues, we aimed to develop and test an easy-to-use, easy-to-adapt, and offline working app using smartphone sensors (GPS and accelerometry) for the quantification of mobility parameters.

methodsAn Android app, a server backend, and a specialized analysis pipeline have been developed (development substudy). Parameters of mobility by the study team members were extracted from the recorded GPS data using existing and newly developed algorithms. Test measurements were performed with participants to complete accuracy and reliability tests (accuracy substudy). Usability was examined by interviewing community-dwelling older adults after 1 week of device use, followed by an iterative app design process (usability substudy).

resultsThe study protocol and the software toolchain worked reliably and accurately, even under suboptimal conditions, such as narrow streets and rural areas. The developed algorithms had high accuracy (97.4% correctness, F

conclusionsBased on accuracy analyses and users' experience with the proposed system for GPS assessments, the developed algorithm showed great potential for app-based estimation of mobility in diverse health research contexts, including mobility patterns of community-dwelling older adults living in rural areas. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12877-021-02739-0.

Indexed as

geographic information systemgeoinformaticsout-of-home mobilityprevention medicinerehabilitation

Identifiers

PMID36862498
PMCPMC10020906
OpenAlexW4313335010

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read8
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.