Video-based analysis of motion skills in simulation-based surgical training

Analysis ofmotionexpertiseisanimportantprobleminmanydomainsincludingsportsandsurgery.Inrecent years,surgicalsimulationhasemergedattheforefrontofnewtechnologiesforimprovingtheeducationand training ofsurgicalresidents.Insimulation-basedsurgicaltraining,akeytaskistoratetheperformanceofthe operators,whichisdonecurrentlybyseniorsurgeons.Thispaperintroducesanovelsolutiontothisproblem through employingvision-basedtechniques.Wedevelopanautomatic,video-basedapproachtoanalyzingthe motion skillsofasurgeoninsimulation-basedsurgicaltraining,whereasurgicalactioniscapturedbymultiple video cameraswithlittleornocalibration,resultinginmultiplevideostreamsofheterogeneousproperties. Typicalmultiple-viewvisiontechniquesareinadequateforprocessingsuchdata.Weproposeanovelapproach that employsbothcanonicalcorrelationanalysis(CCA)andthebag-of-wordsmodeltoclassifytheexpertise levelofthesubjectbasedontheheterogeneousvideostreamscapturingboththemotionofthesubject'shands and theresultantmotionofthetools.Experimentsweredesignedandperformedtovalidatetheproposed approachusingrealisticdatacapturedfromresidentsurgeonsinlocalhospitals.Theresultssuggestthatthe proposedapproachmayprovideapromisingpracticalsolutiontotherealworldproblemevaluatingmotionskills in simulation-basedsurgicaltraining.