Evidence map›Paper›PMID 27688882›Full record

ArticleMovement ecology2016

A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle.

Rory P Wilson, Mark D Holton, James S Walker, Emily L C Shepard, D Mike Scantlebury, Vianney L Wilson, Gwendoline I Wilson, Brenda Tysse, Mike Gravenor, Javier Ciancio and 11 more

Open access · goldAbstract read
In one paragraph

Article in Movement ecology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
7.9field-weighted citation impact, top 4% 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

8 citing papers in PubMed, 23 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

21 authors at 5 institutions in 4 countries.

Rory P WilsonSwansea Lab for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Mark D HoltonVisual Computing, Computer Science, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
James S WalkerVisual Computing, Computer Science, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Emily L C ShepardSwansea Lab for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
D Mike ScantleburySchool of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Medical Biology Centre, 97, Lisburn Road, Belfast, BT9 7BL UK.
Vianney L WilsonSwansea Lab for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Gwendoline I WilsonSwansea Lab for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Brenda TysseSwansea Lab for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Mike GravenorInstitute of Life Science, Swansea University Medical School, Swansea, SA2 8PP UK.
Javier CiancioCentro Nacional Patagonico, Boulevard Brown s/n, Chubut, Argentina.
Melitta A McNarryApplied Sports Science Technology and Medicine Research Centre, College of Engineering, Swansea University, Fabian Way, Swansea, SA1 8EN UK.
Kelly A MackintoshApplied Sports Science Technology and Medicine Research Centre, College of Engineering, Swansea University, Fabian Way, Swansea, SA1 8EN UK.
Lama QasemDepartment of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, Doha, 2713 Qatar.
Frank RosellFaculty of Arts and Sciences, Department of Environmental and Health Studies, Telemark University College, N-3800 Bø i, Telemark, Norway.
Patricia M GrafFaculty of Arts and Sciences, Department of Environmental and Health Studies, Telemark University College, N-3800 Bø i, Telemark, Norway ; Department of Integrative Biology and Biodiversity Research, Institute of Wildlife Biology and Game Management, University of Natural Resources and Life Sciences, Vienna, A-1180 Vienna Austria.
Flavio QuintanaCentro Nacional Patagonico, Boulevard Brown s/n, Chubut, Argentina.
Agustina Gomez-LaichCentro Nacional Patagonico, Boulevard Brown s/n, Chubut, Argentina.
Juan-Emilio SalaCentro Nacional Patagonico, Boulevard Brown s/n, Chubut, Argentina.
Christina C MulvennaSchool of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Medical Biology Centre, 97, Lisburn Road, Belfast, BT9 7BL UK.
Nicola J MarksSchool of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Medical Biology Centre, 97, Lisburn Road, Belfast, BT9 7BL UK.
Mark W JonesVisual Computing, Computer Science, College of Science, Swansea University, Singleton Park, Swansea, SA2 8PP UK.
Swansea University · GBCentro Científico Tecnológico Patagónico · ARQueen's University Belfast · GBTelemark Research Institute · NOQatar University · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe are increasingly using recording devices with multiple sensors operating at high frequencies to produce large volumes of data which are problematic to interpret. A particularly challenging example comes from studies on animals and humans where researchers use animal-attached accelerometers on moving subjects to attempt to quantify behaviour, energy expenditure and condition.

resultsThe approach taken effectively concatinated three complex lines of acceleration into one visualization that highlighted patterns that were otherwise not obvious. The summation of data points within sphere facets and presentation into histograms on the sphere surface effectively dealt with data occlusion. Further frequency binning of data within facets and representation of these bins as discs on spines radiating from the sphere allowed patterns in dynamic body accelerations (DBA) associated with different postures to become obvious.

methodWe examine the extent to which novel, gravity-based spherical plots can produce revealing visualizations to incorporate the complexity of such multidimensional acceleration data using a suite of different acceleration-derived metrics with a view to highlighting patterns that are not obvious using current approaches. The basis for the visualisation involved three-dimensional plots of the smoothed acceleration values, which then occupied points on the surface of a sphere. This sphere was divided into facets and point density within each facet expressed as a histogram. Within each facet-dependent histogram, data were also grouped into frequency bins of any desirable parameters, most particularly dynamic body acceleration (DBA), which were then presented as discs on a central spine radiating from the facet. Greater radial distances from the sphere surface indicated greater DBA values while greater disc diameter indicated larger numbers of data points with that particular value.

conclusionsWe indicate how this approach links behaviour and proxies for energetics and can inform our identification and understanding of movement-related processes, highlighting subtle differences in movement and its associated energetics. This approach has ramifications that should expand to areas as disparate as disease identification, lifestyle, sports practice and wild animal ecology. UCT Science Faculty Animal Ethics 2014/V10/PR (valid until 2017).

Indexed as

G-sphereSpherical plotsTri-axial accelerationVisualisation

Identifiers

PMID27688882
PMCPMC5035456
OpenAlexW2521569614

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.