title: Laparoscopic task recognition using Hidden Markov Models.
abstract: Surgical skills assessment has been paid increased attention over the last few years. Stochastic models such as Hidden Markov Models have recently been adapted to surgery to discriminate levels of expertise. Based on our previous work combining synchronized video and motion analysis we present preliminary results of a HMM laparoscopic task recognizer which aims to model hand manipulations and to identify and recognize simple surgical tasks.
authors.affiliation: Department of Surgical Oncology and Technology, St.Mary's Hospital, Imperial College, London, UK.
authors.forename: Aristotelis
authors.initials: A
authors.lastname: Dosis
authors.forename: Fernando
authors.initials: F
authors.lastname: Bello
authors.forename: Duncan
authors.initials: D
authors.lastname: Gillies
authors.forename: Shabnam
authors.initials: S
authors.lastname: Undre
authors.forename: Rajesh
authors.initials: R
authors.lastname: Aggarwal
authors.forename: Ara
authors.initials: A
authors.lastname: Darzi
mesh_terms: D002983:Clinical Competence / Q000592:standards; D006801:Humans; D010535:Laparoscopy; D008390:Markov Chains; D013536:Suture Techniques / Q000193:education*; D006113:United Kingdom