Explanation: The novel robotic surgical controller developed in my research is the only robotic gripper prototype to offer a surgeon the intuitive ability to remotely grasp an object, and to accurately and realistically replicate the touch feedback that the end effector encounters on the operator’s hand.
I was inspired by my grandmother’s heart surgery to study robotic surgery, which accounts for 80% of certain surgical procedures. Though 652,000 minimally invasive robotic surgeries were performed in 2015, each surgeon operated without the benefit of the sense of touch. Recent meta-analyses of haptic (touch) prototypes have demonstrated that significant (67%) improvements might be realized if a device can be designed which incorporates haptic benefits, with improvement specifically desired for tumor palpation in cancer surgeries and delicate tissue handling during heart surgeries. However, no haptic devices currently exist which enable a robotic surgeon to virtually grasp a remote object intuitively and accurately feel force feedback. I used soft robotics to design and build a prototype operator control glove and surgical grasper incorporating touch feedback. It allows an operator to position a finger at a certain angle, and to have a finger-shaped actuator mimic the surgeon’s finger, generating identical force at both ends. This novel prototype represents the first design to successfully deliver “bio-mirroring” capabilities: haptic input, haptic force feedback, grasping control, a compliant end effector, pliable haptic output and a closed loop control system. This prototype made the first-ever use of soft robotic pneumatic networks in a haptic grasper and was pressurized with an open-sourced electropneumatic control board. It utilizes MATLAB and Arduino to read and control fingertip sensor values. This interdisciplinary robotics experiment combined mechanical engineering, electrical engineering and computer programming. The results demonstrate that the remote actuator was correctly controlled by the user’s hand motions, and haptic feedback was accurately provided to the user. The Flex Input Sensor values predict Flex Output Sensor values with about 93% accuracy and the force measured by the Haptic Input Sensor predicts the force measured by the Haptic Force Feedback Sensor with about 98% accuracy. In order to encourage a vibrant exchange of scientific ideas in my field, I founded the Soft Robotics Technology Group Meetup (www.meetup.com/Soft-Robotics), which currently has over 600 members in the New York Area. I survey relevant academic and entrepreneurial developments, and invite leading figures to speak at our Meetups, so that the engineers, educators, makers and investors in the soft robotics community can share insights. In addition, I founded Paradox Robotics (www.paradoxrobotics.com) to supply a pre-packaged and pre-engineered soft robotics fluidic control board kit, from Harvard University’s open source design. My company assembles and ships a pre-packaged kit of parts to make a pre-tested control board for soft robots, with Harvard’s permission.
Inspiration: My grandmother and mother both suffer from the same congenital heart defect, which inspired me to study the errors in cardiac surgery caused by a lack of haptic (touch) feedback. As part of a school research team project several years ago, we visited Memorial Sloan Kettering, and observed the daVinci Surgical System. I saw how difficult it might be for surgeons to manipulate the robotic surgical device without the benefit of touch. Shortly thereafter, my grandmother’s heart defect required open-chest surgery because robotic minimally invasive surgery (MIS) was not available for her condition.
Thankfully, my grandmother’s surgery was a success, but I was extremely motivated to help advance robotic surgery. My senior year in high school as a summer researcher in Harvard’s Biodesign Lab, I thought back to that experience observing the robotic surgical equipment. I researched haptic sensing, finding that it was not yet standard practice in surgery. The daVinci surgical system represents 100% of the minimally invasive robotic surgery market, and currently offers no haptic feedback capabilities. The surgeons rely on visual feedback.
Three issues indicate that Robotic MIS needs further optimization: (1) Though Robotic MIS represents 80% of prostate surgeries, is far less prevalent in other areas, and it can only be used for less than 10% of certain surgeries such as hernia or thoracic surgery. (2) Robotic surgery techniques have decreased complications from 9% to 5% for some surgeries, but progress is possible as we seek to drive the complication rate from 5% down as close as possible to 0%. (3) Since 2000, there have been significant malfunction-related adverse events reported with negative patient impacts including 1,391 injuries and 144 deaths – those incidents have many causes, but demonstrate that our robotic surgical equipment can still be safer. Recent meta-analyses of haptic (touch) prototypes in experimental robotic surgery settings have demonstrated that significant (67%) improvements might be realized in overall work performance, as well as task completion time, precise force regulation, and error rate reduction surgery if a device can be designed which incorporates a full range of haptic benefits.
With my prototype device’s “bio-mirroring” capabilities, the surgeon’s grasp could be duplicated by the robot with about 93% accuracy, and the force feedback experienced by the surgeon’s finger could be predicted with about 98% accuracy. Specifically, palpation for tumors in cancer surgery and handling delicate tissue during heart surgery are two areas which have been targeted for improvement using surgical touch feedback.
In addition to improving outcomes in robotic surgery, possible other applications for “bio-mirroring“ include industrial handling, disaster relief, rehabilitation, virtual reality entertainment and training.
PRIMARY FOCUS:
Life Science / Healthcare Robotics and Gadgets Stem or Steam Other Minimally Invasive Robotic Surgery
SCHOOL:
Dalton School
INFORMATION
Website for the project