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Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running
The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A si...
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| Published in: | European journal of sport science 2015-07, Vol.15 (5), p.382-390 |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
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| cites | cdi_FETCH-LOGICAL-c4838-5b684932feb7842cf17f44a65ea2fa83ee0b34c59c0851fa79a47ee5b5abbd223 |
| container_end_page | 390 |
| container_issue | 5 |
| container_start_page | 382 |
| container_title | European journal of sport science |
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| creator | Wundersitz, Daniel W. T. Gastin, Paul B. Richter, Chris Robertson, Samuel J. Netto, Kevin J. |
| description | The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging. |
| doi_str_mv | 10.1080/17461391.2014.955131 |
| format | article |
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T. ; Gastin, Paul B. ; Richter, Chris ; Robertson, Samuel J. ; Netto, Kevin J.</creator><creatorcontrib>Wundersitz, Daniel W. T. ; Gastin, Paul B. ; Richter, Chris ; Robertson, Samuel J. ; Netto, Kevin J.</creatorcontrib><description>The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging.</description><identifier>ISSN: 1746-1391</identifier><identifier>EISSN: 1536-7290</identifier><identifier>DOI: 10.1080/17461391.2014.955131</identifier><identifier>PMID: 25196466</identifier><language>eng</language><publisher>England: Routledge</publisher><subject>3D analysis ; Acceleration ; Accelerometry - instrumentation ; Accelerometry - methods ; Adult ; Female ; game analysis ; Humans ; Jogging - physiology ; Male ; methodology ; Monitoring, Ambulatory - instrumentation ; Monitoring, Ambulatory - methods ; Reproducibility of Results ; Signal Processing, Computer-Assisted ; technology ; Walking - physiology ; Young Adult</subject><ispartof>European journal of sport science, 2015-07, Vol.15 (5), p.382-390</ispartof><rights>2014 European College of Sport Science 2014</rights><rights>European College of Sport Science</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4838-5b684932feb7842cf17f44a65ea2fa83ee0b34c59c0851fa79a47ee5b5abbd223</citedby><cites>FETCH-LOGICAL-c4838-5b684932feb7842cf17f44a65ea2fa83ee0b34c59c0851fa79a47ee5b5abbd223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,786,790,27957,27958</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25196466$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wundersitz, Daniel W. T.</creatorcontrib><creatorcontrib>Gastin, Paul B.</creatorcontrib><creatorcontrib>Richter, Chris</creatorcontrib><creatorcontrib>Robertson, Samuel J.</creatorcontrib><creatorcontrib>Netto, Kevin J.</creatorcontrib><title>Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running</title><title>European journal of sport science</title><addtitle>Eur J Sport Sci</addtitle><description>The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging.</description><subject>3D analysis</subject><subject>Acceleration</subject><subject>Accelerometry - instrumentation</subject><subject>Accelerometry - methods</subject><subject>Adult</subject><subject>Female</subject><subject>game analysis</subject><subject>Humans</subject><subject>Jogging - physiology</subject><subject>Male</subject><subject>methodology</subject><subject>Monitoring, Ambulatory - instrumentation</subject><subject>Monitoring, Ambulatory - methods</subject><subject>Reproducibility of Results</subject><subject>Signal Processing, Computer-Assisted</subject><subject>technology</subject><subject>Walking - physiology</subject><subject>Young Adult</subject><issn>1746-1391</issn><issn>1536-7290</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkE9v1DAQxS1ERUvhGyDkIwey-G_iHBCCVQtUlXoocLUmyXjl3SRe7ESr_fZ4lS5HxGlGM7_3ZvQIecPZijPDPvBKlVzWfCUYV6taay75M3LFtSyLStTsee4zUpyYS_IypS1jeSDMC3IpNK9LVZZXZPsLet_56UiDo0CnOI-7YgjzOGFHoW2xxxgGnDDSKVBICVOie4TdeQmTD2Oi3Rz9uKEH6He5vqfbsNmcBjB2NHuOuX9FLhz0CV8_1Wvy8_bmx_pbcf_w9fv6833RKiNNoZvSqFoKh01llGgdr5xSUGoE4cBIRNZI1eq6ZUZzB1UNqkLUjYam6YSQ1-Td4ruP4feMabKDT_nXHkYMc7K8NLzmSoo6o2pB2xhSiujsPvoB4tFyZk8p23PK9pSyXVLOsrdPF-ZmwO6v6BxrBj4uwMH3ePwvU3tz97j-cstYVZqs_7To_ehCHOAQYt_ZCY59iC7C2Ppk5T9f_APeRJ6R</recordid><startdate>20150704</startdate><enddate>20150704</enddate><creator>Wundersitz, Daniel W. 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T. ; Gastin, Paul B. ; Richter, Chris ; Robertson, Samuel J. ; Netto, Kevin J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4838-5b684932feb7842cf17f44a65ea2fa83ee0b34c59c0851fa79a47ee5b5abbd223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>3D analysis</topic><topic>Acceleration</topic><topic>Accelerometry - instrumentation</topic><topic>Accelerometry - methods</topic><topic>Adult</topic><topic>Female</topic><topic>game analysis</topic><topic>Humans</topic><topic>Jogging - physiology</topic><topic>Male</topic><topic>methodology</topic><topic>Monitoring, Ambulatory - instrumentation</topic><topic>Monitoring, Ambulatory - methods</topic><topic>Reproducibility of Results</topic><topic>Signal Processing, Computer-Assisted</topic><topic>technology</topic><topic>Walking - physiology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wundersitz, Daniel W. T.</creatorcontrib><creatorcontrib>Gastin, Paul B.</creatorcontrib><creatorcontrib>Richter, Chris</creatorcontrib><creatorcontrib>Robertson, Samuel J.</creatorcontrib><creatorcontrib>Netto, Kevin J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of sport science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wundersitz, Daniel W. T.</au><au>Gastin, Paul B.</au><au>Richter, Chris</au><au>Robertson, Samuel J.</au><au>Netto, Kevin J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running</atitle><jtitle>European journal of sport science</jtitle><addtitle>Eur J Sport Sci</addtitle><date>2015-07-04</date><risdate>2015</risdate><volume>15</volume><issue>5</issue><spage>382</spage><epage>390</epage><pages>382-390</pages><issn>1746-1391</issn><eissn>1536-7290</eissn><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><abstract>The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging.</abstract><cop>England</cop><pub>Routledge</pub><pmid>25196466</pmid><doi>10.1080/17461391.2014.955131</doi><tpages>9</tpages></addata></record> |
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| ispartof | European journal of sport science, 2015-07, Vol.15 (5), p.382-390 |
| issn | 1746-1391 1536-7290 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1681914329 |
| source | SPORTDiscus with Full Text |
| subjects | 3D analysis Acceleration Accelerometry - instrumentation Accelerometry - methods Adult Female game analysis Humans Jogging - physiology Male methodology Monitoring, Ambulatory - instrumentation Monitoring, Ambulatory - methods Reproducibility of Results Signal Processing, Computer-Assisted technology Walking - physiology Young Adult |
| title | Validity of a trunk-mounted accelerometer to assess peak accelerations during walking, jogging and running |
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