Evidence map›Paper›PMID 26225973›Full record

Trial reportSensors (Basel, Switzerland)2015

A Comparative Study on the Suitability of Smartphones and IMU for Mobile, Unsupervised Energy Expenditure Calculi.

Angel Ruiz-Zafra, Eva Orantes-González, Manuel Noguera, Kawtar Benghazi, Jose Heredia-Jimenez

Abstract readClinical TrialComparative Study
In one paragraph

Trial report in Sensors (Basel, Switzerland), 2015. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Angel Ruiz-ZafraUniversity of Granada, Avda. del Hospicio, Granada 18071, Spain. angelr@ugr.es.
Eva Orantes-GonzálezUniversity of Granada, Avda. del Hospicio, Granada 18071, Spain. maevor@ugr.es.
Manuel NogueraUniversity of Granada, Avda. del Hospicio, Granada 18071, Spain. mnoguera@ugr.es.
Kawtar BenghaziUniversity of Granada, Avda. del Hospicio, Granada 18071, Spain. benghazi@ugr.es.
Jose Heredia-JimenezUniversity of Granada, Avda. del Hospicio, Granada 18071, Spain. herediaj@ugr.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The metabolic equivalent of task (MET) is currently the most used indicator for measuring the energy expenditure (EE) of a physical activity (PA) and has become an important measure for determining and supervising a person's state of health. The use of new devices which are capable of measuring inertial movements by means of built-in accelerometers enable the PA to be measured objectively on the basis of the reckoning of "counts". These devices are also known as inertial measurement units (IMUs) and each count is an aggregated value indicating the intensity of a movement and can be used in conjunction with other parameters to determine the MET rate of a particular physical activity and thus it's associated EE. Various types of inertial devices currently exist that enable count calculus and physical activity to be monitored. The advent of mobile devices, such as smartphones, with empowered computation capabilities and integrated inertial sensors, has enabled EE to be measure in a distributed, ubiquitous and natural way, thereby overcoming the reluctance of users and practitioners associated with in-lab studies. From the point of view of the process analysis and infrastructure needed to manage data from inertial devices, there are also various differences in count computing: extra devices are required, out-of-device processing, etc. This paper presents a study to discover whether the estimation of energy expenditure is dependent on the accelerometer of the device used in measurements and to discover the suitability of each device for performing certain physical activities. In order to achieve this objective, we have conducted several experiments with different subjects on the basis of the performance of various daily activities with different smartphones and IMUs.

Indexed as

Energy MetabolismSmartphoneAccelerometryAdultHumansMotor ActivityYoung Adultaccelerometersenergy expenditureMETmetabolic equivalent of taskmobilephysical activitysmartphones

Identifiers

PMID26225973
PMCPMC4570320

What OpenQuestion holds

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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.