Borrowing ideas from speech recognition research, Johns Hopkins computer scientists are building mathematical models to represent the safest and most effective ways to perform surgery, including tasks such as suturing, dissecting and joining tissue.
The team's long-term goal is to develop an objective way of evaluating a surgeon's work and to help doctors improve their operating room skills. Ultimately, the research also could enable robotic surgical tools to perform with greater precision.
The project, supported by a three-year National Science Foundation grant, has yielded promising early results in modeling suturing work. The researchers performed the suturing with the help of a robotic surgical device, which recorded the movements and made them available for computer analysis.
"Surgery is a skilled activity, and it has a structure that can be taught and acquired," said Gregory D. Hager, a professor of computer science in the university's Whiting School of Engineering and principal investigator on the project. "We can think of that structure as the language of surgery.' To develop mathematical models for this language, we're borrowing techniques from speech recognition technology and applying them to motion recognition and skills assessment."
Complicated surgical tasks, Hager said, unfold in a series of steps that resemble the way that words, sentences and paragraphs are used to convey language. "In speech recognition research, we break these down to their most basic sounds, called phonemes," he said. "Following that example, our team wants to break surgical procedures down to simple gestures that can be represented mathematically by computer software."
With that information in hand, the computer scientists hope to be able to recognize when a surgical task is being performed well and also to identify which movements can lead to operating room problems. Just as a speech recognition program might call a
Contact: Phil Sneiderman
Johns Hopkins University