Title:
Computational Modeling and Enhancement of Human Skill

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hager.mp4 (451.36 MB)
hager_videostream.html (985 B)
transcription.txt (57.13 KB)
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Hager, Gregory D.
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http://hdl.handle.net/1853/52724
Abstract
With the rapidly growing popularity of the Intuitive Surgical da Vinci system, robotic minimally invasive surgery (RMIS) has crossed the threshold from the laboratory to the real world. There are now hundreds of thousands of human-guided robotic surgeries performed every year, and the number is growing rapidly. This is a unique example of the growing paradigm of human-machine collaborative systems—namely systems of machines and computers collaborating with people to perform tasks that neither can perform as effectively alone. While designed to be an amplifier of human ability, collaborative systems like the da Vinci pose a number of new challenges. In particular, the learning curve is steep and involves mastery of a new and rapidly evolving set of skills and techniques. Yet, at the same time, the availability of easily acquired data also creates new opportunities to create new engineering paradigms for modeling, evaluating, and improving human skill. In this talk, I will describe our work toward developing effective human-machine collaborative teams. I will spend most of the talk discussing approaches to modeling complex manipulation tasks within in the context of surgery. By creating models for the “Language of Surgery,” I will show that we are able to evaluate the style and efficiency of surgical motion. These models also lead naturally to methods for supporting, or even automating, component actions in surgery as well as in other domains. At the end of the talk, I will briefly touch on our recent work, building on these ideas, to develop collaborative systems for manufacturing. This talk includes joint work with Sanjeev Khudanpur and Rene Vidal.
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Date Issued
2014-10-22
Extent
56:07 minutes
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Lecture
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