DaVinci Operation
Don't worry Cavity Sam, the da Vinci robot is here to remove that broken funny bone!

Modern life teaches us funny lessons like: if you can't win at a child's board game, use a multimillion dollar robot to cheat. PhD students at John Hopkins University's Lab for Computational Sensing and Robotics (LCSR) ran into some trouble playing the classic board game Operation which requires you to remove tiny plastic organs from 'Cavity Sam' without triggering his electric alarm system and killing him. Their failure is a little daunting considering these guys are the next generation of surgical innovators. To overcome their limitations, those students hooked 'Sam' up to the da Vinci robot system from Intuitive Surgical. The video below shows the results. While this was all just a good natured joke, I'm glad the da Vinci robot and LCSR are getting some decent publicity from it. These robots, and the surgeons who use them, are saving thousands of lives each year and pushing us towards the future of medicine.

We've covered the da Vinci system extensively in the past. These bots are becoming the standard for prostate surgery and innovators like Catherine Mohr are pushing for a future where robots are involved in a much larger portion of operations. While they are most often operated remotely by trained surgeons, more and more automated sequences are available. Smaller incisions, more precise motions, and a reduction in human error - you can see why the surgical robots are so popular.

Hopefully the John Hopkins video will increase their popularity even further. So kudos to the LCSR team for putting that little gem together. Speaking of which, I urge you to check out the work of Carol Reiley, Tom Tantillo, and Kel Guerin - the stars and producer behind the video. What these guys lack in acting they more than make up for in robotic surgery prowess. I can't wait until their next video comes out. Maybe they'll teach da Vinci to put tiny stickers on matchbox cars. I wasn't any good at that during childhood either .

[screen capture and video credit: John Hopkins University]
[source: John Hopkins University Lab for Computational Sensing and Robotics]