Evidence map›Paper›PMID 28582259›Full record

ArticleJMIR rehabilitation and assistive technologies2015

Mobile Jump Assessment (mJump): A Descriptive and Inferential Study.

Alvaro Mateos-Angulo, Alejandro Galán-Mercant, Antonio Cuesta-Vargas

Open access · goldAbstract read
In one paragraph

Article in JMIR rehabilitation and assistive technologies, 2015. 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
0.3field-weighted citation impact, top 42% 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, 8 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Alvaro Mateos-AnguloUniversidad de Malaga, Insituto de Investigación Biomedica de Malaga, Malaga, Spain.ORCID http://orcid.org/0000-0002-8561-1913
Alejandro Galán-MercantUniversidad de Malaga, Insituto de Investigación Biomedica de Malaga, Malaga, Spain.ORCID http://orcid.org/0000-0003-3581-0372
Antonio Cuesta-VargasUniversidad de Malaga, Insituto de Investigación Biomedica de Malaga, Malaga, Spain.ORCID http://orcid.org/0000-0002-1918-3711
Instituto de Investigación Biomédica de Málaga · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVertical jump tests are used in athletics and rehabilitation to measure physical performance in people of different age ranges and fitness. Jumping ability can be analyzed through different variables, and the most commonly used are fly time and jump height. They can be obtained by a variety of measuring devices, but most are limited to laboratory use only. The current generation of smartphones contains inertial sensors that are able to record kinematic variables for human motion analysis, since they are tools for easy access and portability for clinical use.

objectiveThe aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S, the lower limbs strength through a manual dynamometer, and the jump variables obtained with a contact mat in the squat jump and countermovement jump tests (fly time and jump height) from a cohort of healthy people.

methodsA cross sectional study was conducted on a population of healthy young adults. Twenty-seven participants performed three trials (n=81 jumps) of squat jump and countermovement jump tests. Acceleration variables were measured through a smartphone's inertial sensor. Additionally, jump variables from a contact mat and lower limbs dynamometry were collected.

resultsIn the present study, the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S, dynamometry of lower limbs with a handheld dynamometer, and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. The development of the execution has been described, examined and identified in a squat jump test and countermovement jump test under acceleration variables that were obtained with the smartphone.

conclusionsThe built-in iPhone 4S inertial sensor is able to measure acceleration variables while performing vertical jump tests for the squat jump and countermovement jump in healthy young adults. The acceleration kinematics variables derived from the smartphone's inertial sensor are higher in the countermovement jump test than the squat jump test.

Indexed as

countermovement jumpinertial sensorsmartphonesquat jump

Identifiers

PMID28582259
PMCPMC5454547
OpenAlexW1911704687

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.