Search PubMed⌕ Search

PubMed · 15718711

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.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Aristotelis Dosis, Fernando Bello, Duncan Gillies, Shabnam Undre, Rajesh Aggarwal, Ara Darzi. 2005. Laparoscopic task recognition using Hidden Markov Models.. https://pubmed.ncbi.nlm.nih.gov/15718711/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Emergent themes in the sustainability of primary health care innovation.

A synthesis of the findings of the five studies of sustainability of primary health care innovation across six domains (political, institutional, financial, economic, client and workforce) yielded three main themes. These were: the importance of social relationships, networks and champions; the effect of political, financial and societal forces; and the motivation and capacity of agents within the system. The need for routine assessment of the sustainability of primary health care innovations is discussed. Given the dearth of literature on the sustainability of primary health care innovation, there is potential to develop a program of research directed towards a future synthesis of evidence.

Clinical Competence↗