Carol E. Reiley 1 Henry C. Lin 1 , Balakrishnan Varadarajan 2 , Balazs Vagvolgyi 1 , Sanjeev Khudanpur 2 , David D. Yuh 3 , Gregory D. Hager 1 1 Engineering Research Center for Computer-Integrated Surgical Systems and Technology, The Johns Hopkins University 2 Center for Speech Language Processing, The Johns Hopkins University 3 Division of Cardiac Surgery, The Johns Hopkins Medical Institutions MMVR January 31 st , 2008 Automatic Recognition of Surgical Motions Using Statistical Modeling for Capturing Variability
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Automatic Recognition of Surgical Motions Using Statistical Modeling for Capturing Variability
Automatic Recognition of Surgical Motions Using Statistical Modeling for Capturing Variability. Carol E. Reiley 1 Henry C. Lin 1 , Balakrishnan Varadarajan 2 , Balazs Vagvolgyi 1 , Sanjeev Khudanpur 2 , David D. Yuh 3 , Gregory D. Hager 1 - PowerPoint PPT Presentation
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Carol E. Reiley1
Henry C. Lin1, Balakrishnan Varadarajan2, Balazs Vagvolgyi1, Sanjeev Khudanpur2, David D. Yuh3, Gregory D. Hager1
1Engineering Research Center for Computer-Integrated Surgical Systems and Technology, The Johns Hopkins University
2Center for Speech Language Processing, The Johns Hopkins University3Division of Cardiac Surgery, The Johns Hopkins Medical Institutions
MMVR January 31st, 2008
Automatic Recognition of Surgical Motions Using Statistical Modeling for
Capturing Variability
Introduction
• Our Goal
• Automatically segment and recognize core surgical motion segments (surgemes)
• Capture the variability of a surgeon’s movement techniques using statistical methods
Introduction
• Given a surgical task, a single user tends to use similar movement patterns
Lin 2005 Miccai
Introduction
• Different users demonstrate more variability to complete the same surgical task
• Our goal is to identify core surgical motions versus error/unintentional motion