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dc.contributor.authorMalpani, Anand
dc.date2015
dc.date.accessioned2017-10-03T19:55:42Z
dc.date.available2017-10-03T19:55:42Z
dc.date.issued2016
dc.identifier.citationMalpani, Anand. (2016). Directed Feedback for Simulation-based Training in Robot-assisted Minimally Invasive Surgery. (Link Foundation Fellowship Final Reports: Modeling, Simulation, and Training Program.) Retrieved from The Scholarship Repository of Florida Institute of Technology website: https://repository.lib.fit.edu/en_US
dc.identifier.urihttp://hdl.handle.net/11141/1701
dc.descriptionSurgical training; virtual reality simulationen_US
dc.description.abstractSurgical educators have recommended the need for objective and automated teaching tools for technical skills training. Current training platforms provide automated or manual global assessments that are based on postoperative performance review. Approaches like these lack task segment specific feedback that informs the trainee of where, why and what went wrong that led to the lower performance scores, if at all. Coaching with targeted feedback is crucial not only for new trainees, but also equally critical for experienced surgeons to retain their skills and maintain higher levels of performance. The objective of my thesis project is to develop a virtual coach that can provide directed feedback to the trainee. This includes step-by-step performance evaluation, skill deficiency or error detection, and relevant demonstration presentation. Our framework mainly consists of three components – a) task segmentation, b) segment-level evaluation, and c) feedback generation for targeted practice and improvement.en_US
dc.language.isoen_USen_US
dc.rights© 2016. the authoren_US
dc.rights.urihttps://repository.lib.fit.edu/handle/11141/1665en_US
dc.titleDirected Feedback for Simulation-based Training in Robot-assisted Minimally Invasive Surgeryen_US
dc.typeTechnical Reporten_US
thesis.degree.levelDoctoral
thesis.degree.disciplineComputer Science
thesis.degree.grantorJohn Hopkins University


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