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A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle / Mark, Jones; Michael, Gravenor; Mark, Holton; Rory, Wilson; Emily, Shepard; Melitta, McNarry; Kelly, Mackintosh

Movement Ecology, Volume: 4, Issue: 1

Swansesa University Authors: Mark, Jones, Michael, Gravenor, Mark, Holton, Rory, Wilson, Emily, Shepard, Melitta, McNarry, Kelly, Mackintosh

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Abstract

Background We 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 accelerome...

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Published in: Movement Ecology
ISSN: 2051-3933
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa30318
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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. Results The approach taken effectively concatenated 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. Method We 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. Conclusions We 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.</abstract><type>Journal Article</type><journal>Movement Ecology</journal><volume>4</volume><journalNumber>1</journalNumber><publisher/><issnElectronic>2051-3933</issnElectronic><keywords/><publishedDay>23</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2016</publishedYear><publishedDate>2016-09-23</publishedDate><doi>10.1186/s40462-016-0088-3</doi><url/><notes/><college>COLLEGE NANME</college><department>Computer Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution>Swansea University</institution><lastEdited>2016-11-24T10:28:23.1558682</lastEdited><Created>2016-10-03T15:16:14.8577062</Created><path><level id="1">College of Science</level><level id="2">Computer Science</level></path><authors><author><firstname>Mark</firstname><surname>Jones</surname><orcid>0000-0001-8991-1190</orcid><order>1</order></author><author><firstname>Michael</firstname><surname>Gravenor</surname><orcid>0000-0003-0710-0947</orcid><order>2</order></author><author><firstname>Mark</firstname><surname>Holton</surname><orcid>0000-0001-8834-3283</orcid><order>3</order></author><author><firstname>Rory</firstname><surname>Wilson</surname><orcid>0000-0003-3177-0177</orcid><order>4</order></author><author><firstname>Emily</firstname><surname>Shepard</surname><orcid>0000-0001-7325-6398</orcid><order>5</order></author><author><firstname>Melitta</firstname><surname>McNarry</surname><orcid>0000-0003-0813-7477</orcid><order>6</order></author><author><firstname>Kelly</firstname><surname>Mackintosh</surname><orcid>0000-0003-0355-6357</orcid><order>7</order></author></authors><documents><document><originalFilename>gSpheres2016.pdf</originalFilename><uploaded>2016-10-03T15:18:33.3400000</uploaded><type>Output</type><contentLength>2505091</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><action/><embargoDate>2016-10-03T00:00:00.0000000</embargoDate><documentNotes>&#xA9; 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated</documentNotes><copyrightCorrect>true</copyrightCorrect></document></documents></rfc1807>
spelling 2016-11-24T10:28:23.1558682 v2 30318 2016-10-03 A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 70a544476ce62ba78502ce463c2500d6 0000-0003-0710-0947 Michael Gravenor Michael Gravenor true false 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 54729295145aa1ea56d176818d51ed6a 0000-0001-7325-6398 Emily Shepard Emily Shepard true false 062f5697ff59f004bc8c713955988398 0000-0003-0813-7477 Melitta McNarry Melitta McNarry true false bdb20e3f31bcccf95c7bc116070c4214 0000-0003-0355-6357 Kelly Mackintosh Kelly Mackintosh true false 2016-10-03 SCS Background We 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. Results The approach taken effectively concatenated 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. Method We 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. Conclusions We 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. Journal Article Movement Ecology 4 1 2051-3933 23 9 2016 2016-09-23 10.1186/s40462-016-0088-3 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2016-11-24T10:28:23.1558682 2016-10-03T15:16:14.8577062 College of Science Computer Science Mark Jones 0000-0001-8991-1190 1 Michael Gravenor 0000-0003-0710-0947 2 Mark Holton 0000-0001-8834-3283 3 Rory Wilson 0000-0003-3177-0177 4 Emily Shepard 0000-0001-7325-6398 5 Melitta McNarry 0000-0003-0813-7477 6 Kelly Mackintosh 0000-0003-0355-6357 7 gSpheres2016.pdf 2016-10-03T15:18:33.3400000 Output 2505091 application/pdf Accepted Manuscript true 2016-10-03T00:00:00.0000000 © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated true
title A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
spellingShingle A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
Mark, Jones
Michael, Gravenor
Mark, Holton
Rory, Wilson
Emily, Shepard
Melitta, McNarry
Kelly, Mackintosh
title_short A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
title_full A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
title_fullStr A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
title_full_unstemmed A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
title_sort A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle
author_id_str_mv 2e1030b6e14fc9debd5d5ae7cc335562
70a544476ce62ba78502ce463c2500d6
0e1d89d0cc934a740dcd0a873aed178e
017bc6dd155098860945dc6249c4e9bc
54729295145aa1ea56d176818d51ed6a
062f5697ff59f004bc8c713955988398
bdb20e3f31bcccf95c7bc116070c4214
author_id_fullname_str_mv 2e1030b6e14fc9debd5d5ae7cc335562_***_Mark, Jones
70a544476ce62ba78502ce463c2500d6_***_Michael, Gravenor
0e1d89d0cc934a740dcd0a873aed178e_***_Mark, Holton
017bc6dd155098860945dc6249c4e9bc_***_Rory, Wilson
54729295145aa1ea56d176818d51ed6a_***_Emily, Shepard
062f5697ff59f004bc8c713955988398_***_Melitta, McNarry
bdb20e3f31bcccf95c7bc116070c4214_***_Kelly, Mackintosh
author Mark, Jones
Michael, Gravenor
Mark, Holton
Rory, Wilson
Emily, Shepard
Melitta, McNarry
Kelly, Mackintosh
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container_title Movement Ecology
container_volume 4
container_issue 1
publishDate 2016
institution Swansea University
issn 2051-3933
doi_str_mv 10.1186/s40462-016-0088-3
college_str College of Science
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hierarchy_top_title College of Science
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hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
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description Background We 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. Results The approach taken effectively concatenated 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. Method We 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. Conclusions We 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.
published_date 2016-09-23T03:47:31Z
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