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dc.contributor.authorDavidson, Pavel
dc.contributor.authorVirekunnas, Heikki
dc.contributor.authorSharma, Dharmendra
dc.contributor.authorPiché, Robert
dc.contributor.authorCronin, Neil
dc.date.accessioned2019-04-08T11:06:28Z
dc.date.available2019-04-08T11:06:28Z
dc.date.issued2019fi
dc.identifier.citationDavidson, P., Virekunnas, H., Sharma, D., Piché, R., & Cronin, N. (2019). Continuous Analysis of Running Mechanics by Means of an Integrated INS/GPS Device. <em>Sensors</em>, 19 (6), 1480. <a href="https://doi.org/10.3390/s19061480">doi:10.3390/s19061480</a>fi
dc.identifier.otherTUTKAID_81073
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/63432
dc.description.abstractThis paper describes a single body-mounted sensor that integrates accelerometers, gyroscopes, compasses, barometers, a GPS receiver, and a methodology to process the data for biomechanical studies. The sensor and its data processing system can accurately compute the speed, acceleration, angular velocity, and angular orientation at an output rate of 400 Hz and has the ability to collect large volumes of ecologically-valid data. The system also segments steps and computes metrics for each step. We analyzed the sensitivity of these metrics to changing the start time of the gait cycle. Along with traditional metrics, such as cadence, speed, step length, and vertical oscillation, this system estimates ground contact time and ground reaction forces using machine learning techniques. This equipment is less expensive and cumbersome than the currently used alternatives: Optical tracking systems, in-shoe pressure measurement systems, and force plates. Another advantage, compared to existing methods, is that natural movement is not impeded at the expense of measurement accuracy. The proposed technology could be applied to different sports and activities, including walking, running, motion disorder diagnosis, and geriatric studies. In this paper, we present the results of tests in which the system performed real-time estimation of some parameters of walking and running which are relevant to biomechanical research. Contact time and ground reaction forces computed by the neural network were found to be as accurate as those obtained by an in-shoe pressure measurement system.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherMDPI AG
dc.relation.ispartofseriesSensors
dc.rightsCC BY 4.0
dc.subject.otherbiomekaniikkafi
dc.subject.otherjuoksufi
dc.subject.othermittauslaitteetfi
dc.subject.othersatelliittipaikannusfi
dc.subject.otherkoneoppiminenfi
dc.subject.otherneuroverkotfi
dc.subject.othergait analysisfi
dc.subject.otherINS/GPSfi
dc.subject.othermachine learningfi
dc.subject.otherneural networksfi
dc.subject.othersports equipmentfi
dc.subject.othervelocity measurementfi
dc.titleContinuous Analysis of Running Mechanics by Means of an Integrated INS/GPS Devicefi
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201903292010
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.contributor.oppiaineBiomekaniikka
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2019-03-29T13:15:10Z
dc.description.reviewstatuspeerReviewed
dc.relation.issn1424-8220
dc.relation.numberinseries6
dc.relation.volume19
dc.type.versionpublishedVersion
dc.rights.copyright© 2019 The Authors
dc.rights.accesslevelopenAccessfi
dc.format.contentfulltext
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.3390/s19061480


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