View source for Publications:Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems

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{{PublicationSetupTemplate|Author=Anita Sant'Anna, Nicholas Wickström
|PID=235544
|Name=Sant'Anna, Anita (anisan) (0000-0002-3495-2961) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Wickström, Nicholas (nicholas) (0000-0002-4143-2948) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938))
|Title=Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems
|PublicationType=Conference Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=
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|HostPublication=Pervasive Health 2009 : 3rd International Conference on Pervasive Computing Technologies for Healthcare
|Conference=3rd International Conference on Pervasive Computing Technologies for Healthcare - Pervasive Health 2009, PCTHealth 2009, London, 1-3 April, 2009
|StartPage=1
|EndPage=8
|Year=2009
|Edition=
|Pages=
|City=Piscataway, N.J.
|Publisher=IEEE Press
|Series=
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|ISBN=978-963-9799-42-4
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|DOI=http://dx.doi.org/10.4108/ICST.PERVASIVEHEALTH2009.5913
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|PMID=
|ScopusId=2-s2.0-70350746653
|NBN=urn:nbn:se:hh:diva-85
|LocalId=
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|Keywords=gait analysis;accelerometer;motion language;motion primitives
|Categories=Annan elektroteknik och elektronik (20299)
|ResearchSubjects=
|Projects=SELIES
|Notes=<p>©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.</p>
|Abstract=<p>The advances in sensing technology provide us with the opportunity to develop mobile and unobtrusive systems to continuously gather gait data. Accelerometers have been shown to be an adequate choice for recording human motion data. For that reason, many previous works have investigated the use of accelerometers for gait analysis. Previous works were able to extract either static temporal information or dynamic general information about the gait patterns. This work aims at extracting both static and dynamic information from acceleration signals. The ability to extract information about the dynamics of gait is exemplified with a novel symmetry measure. The method presented here is based on the motion language approach. A method based on peak detection was chosen as a reference, which we compare to our method. A Gait Rite pressure sensitive mat was used to detect heel-strike and toe-off ground truths. Results show that the proposed approach is as accurate as, more robust than, and conveys more information than the reference method.</p>
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|CreatedDate=2009-09-16
|PublicationDate=2009-09-18
|LastUpdated=2016-03-09
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:235544}}
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