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dc.contributor.authorOLeary, Niall
dc.contributor.authorByrne, D. T.
dc.contributor.authorO'Connor, A. H.
dc.contributor.authorShalloo, L.
dc.date.accessioned2021-03-02T21:01:59Z
dc.date.available2020-02-26en
dc.date.issued2020-05
dc.date.submitted2019-12-30en
dc.identifier.issn0022-0302en
dc.identifier.urihttps://hdl.handle.net/10182/13499
dc.description.abstractLocomotion scoring is time consuming and is not commonly completed on farms. Farmers also underestimate their herds' lameness prevalence, a knowledge gap that impedes lameness management. Automation of lameness detection could address this knowledge gap and facilitate improved lameness management. The literature pertinent to adding lameness detection to accelerometers is reviewed in this paper. Options for lameness detection systems are examined including the choice of sensor, raw data collected, variables extracted, and statistical classification methods used. Two categories of variables derived from accelerometer-based systems are examined. These categories are behavior measures such as lying and measures of gait. For example, one measure of gait is the time a leg is swinging during a gait cycle. Some behavior-focused studies have reported accuracy levels of greater than 80%. Cow gait measures have been investigated to a lesser extent than behavior. However, classification accuracies as high as 91% using gait measures have been reported with hardware likely to be practical for commercial farms. The need for even higher accuracy and potential barriers to adoption are discussed. Significant progress is still required to realize a system with sufficient specificity and sensitivity. Lameness detection systems using 1 accelerometer per cow and a resolution lower than 100 Hz with gait measurement functions are suggested to balance cost and data requirements. However, gait measurement using accelerometers is rather underdeveloped. Therefore, a high priority should be given to the development of novel gait measures and testing their ability to differentiate lame from nonlame cows.en
dc.format.extent3895-3911en
dc.language.isoen
dc.publisherFederation of Animal Science Societies (FASS) and Elsevier on behalf of the American Dairy Science Association
dc.relationThe original publication is available from - Federation of Animal Science Societies (FASS) and Elsevier on behalf of the American Dairy Science Association - https://doi.org/10.3168/jds.2019-17123en
dc.relation.urihttps://doi.org/10.3168/jds.2019-17123en
dc.rights© 2020 American Dairy Science Association® and the Authors
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectaccelerometeren
dc.subjectlamenessen
dc.subjectwelfareen
dc.subjectautomateden
dc.subjectDairy & Animal Scienceen
dc.subject.meshAnimalsen
dc.subject.meshCattleen
dc.subject.meshCattle Diseasesen
dc.subject.meshLameness, Animalen
dc.subject.meshBehavior, Animalen
dc.subject.meshDairyingen
dc.subject.meshAccelerometryen
dc.titleInvited review: Cattle lameness detection with accelerometersen
dc.typeJournal Article
lu.contributor.unitLincoln University
lu.contributor.unitFaculty of Agribusiness and Commerce
lu.contributor.unitDepartment of Land Management and Systems
dc.identifier.doi10.3168/jds.2019-17123en
dc.subject.anzsrc070202 Animal Growth and Developmenten
dc.subject.anzsrc10 Technologyen
dc.relation.isPartOfJournal of Dairy Scienceen
pubs.issue5en
pubs.organisational-group/LU
pubs.organisational-group/LU/Faculty of Agribusiness and Commerce
pubs.organisational-group/LU/Faculty of Agribusiness and Commerce/LAMS
pubs.publication-statusPublisheden
pubs.volume103en
dc.identifier.eissn1525-3198en
dc.rights.licenceAttribution-NonCommercial-NoDerivativesen


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