Mark Connick, Emma Beckman, Sean Tweedy The University of ...
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Validation of a class allocation method for wheelchair track athletes with impaired strength – a proof of concept study Mark Connick, Emma Beckman, Sean Tweedy The University of Queensland, Brisbane, Australia Photo by Simon Bruty
Transcript of Mark Connick, Emma Beckman, Sean Tweedy The University of ...
Validationofaclassallocationmethodforwheelchairtrackathleteswithimpairedstrength– aproofofconceptstudy
MarkConnick,EmmaBeckman,SeanTweedy
TheUniversityofQueensland,Brisbane,AustraliaPhotobySimonBruty
Von Winterfeldt (2013). Proc. Natl. Acad. Sci. U.S.A. 2013 Aug 20; 110(Suppl 3): 14055–14061
EVIDENCE‐BASEDDECISIONMAKING
• Similaritieswithevidence‐basedmedicine?
• Centraltenets?
• Howshouldweproceed?
SCIENTIFICBASIS?
DECISION‐MAKINGINTHECURRENTSYSTEM
BASEDONCLINICALREASONING
Performance
EVIDENCE‐BASEDSYSTEM
TRANSPARENT,VALIDATEDDECISIONS
IDENTIFICATIONOFIMPAIRMENTTESTS
Isometricstrengthmeasure
PerformanceOutcome
Top‐Speed(0‐15m)correlation
Top‐Speed(Absolute)correlation
StrongestForearmPronation 0.70* 0.79*WeakestForearmPronation 0.70* 0.79*StrongestArmExtension 0.83* 0.88*WeakestArmExtension 0.81* 0.87*
IsolatedTrunk 0.54* 0.61*Arm+Trunk 0.73* 0.78*
• 32International‐levelwheelchairtrackracers
• ClassesT54‐T51
• Sixisometricstrengthtests
Connick,M.J.,Beckman,E.,Vanlandewijck,Y.,Malone,L.,Blomqvist,S.andTweedy,S.(Underreview).Novelisometricstrength measuresproduceavalidandevidence‐basedclassificationstructureforwheelchairtrackracing:Aclusteranalysis.BritishJournalofSportsMedicine
• 4clusters• Differencesfoundinthe6strengthtestsand2performance‐relatedoutcomes
IDENTIFICATIONOFACLASSSTRUCTURE
AIM
Toevaluatethevalidityofstatisticalrecommendersystemsforallocatingclassinwheelchairtrackracingathletes.
• K-nearest neighbour• Discriminant analysis• Artificial Neural Network• Naïve Bayes• Classification Decision Tree
METHODS
Original Data
Sampling n = 1200 (Gaussian Copula)
Cluster analysis (k = 4)
Evaluate recommender
systems (10-fold cross validation)
Recommender system
Final Prediction
RESULTS
RESULTS
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k‐nearestneighbour
discriminantanalysis
artificialneuralnetwork
classificationtree
naïvebayes
Error(%
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Classificationmethod
METHOD
Original Data
Recommender1
Sampling n = 1200
(Gaussian Copula)
Cluster analysis (k = 4)
Evaluate recommender
systems
Recommender2
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Majority vote Final predictions
Recommender Final Prediction
Recommender3
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k‐nearestneighbour
discriminantanalysis
artificialneuralnetwork
ensemble
Error(%
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Classificationmethod
RESULTS
• Inthispopulation,statisticalrecommendersystemsprovidevalidtoolsthatclassifierscanusetoallocateclass
• However,thiswasproof‐of‐conceptandphilosophicaldiscussionsareneeded– Potentialtranslationofthesemethods
• Preciseparametersmustbecalculatedinalarge‐scalestudy(i.e.testcloseto100%ofthepopulation)
• Influenceoftrainingandintentionalmisrepresentation• Remember,retainexpertopinionandathletecontext
DISCUSSION
THANKYOU
Acknowledgments:
• InternationalParalympicCommittee• TheZayhed HigherOrganisation forHumanitarianCareandSpecialNeeds• Ergotest• Theathletes
• SeanTweedy,MarkConnickandEmmaBeckmanaremembersoftheIPCClassificationResearchandDevelopmentCentre(PhysicalImpairments),whichissupportedbytheInternationalParalympicCommittee.
