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Laparoscopic Surgery Training System.ppt
- 1. Laparoscopic Surgery Training System MediTronics Inc. CEO Alexander Hahn CTO Mark Jung CFO Han-Lim Lee April 2007
- 2. Roles in Project Alexander Hahn (CEO) - Software developer, Technical writing Mark Jung (CTO) - Software and Hardware developer, Finance Management Han-Lim Lee (CFO) - Hardware developer, Time management
- 3. Presentation Outline • Background • Goals • Proposed Solution • System Overview • Hardware • Software • Business Case • Budget/Timeline • Conclusion
- 4. What’s Laparoscopic Surgery? Minimally invasive surgery Gas-inflated abdomen Laparoscope and tools
- 5. Why Laparoscopic Surgery? Small incision Speed up recovery times Minimize post- operative pain Reduce the chances of infection Minimize the size of scars
- 7. The Problems Difficulty in use of the tools
- 8. Current Systems in the market Pure simulation software - Limitation in getting hands-on experience - Lack of physical feeling Pure physical training system - No automated feedback - Eye examination required
- 9. Goals Providing an physical training system Providing an automated feedback & evaluation system A hybrid training system of physical and virtual feature
- 13. System Overview Sensor feedback circuitry
- 17. Overall System
- 18. Hardware Outline Hardware System Overview Force during surgeries FSR vs Strain Gauge FSR Verification Transmitter and Receiver Circuit Alternative Design Option Possible Future Work
- 20. Force During Surgeries Highest Force Peak = 2.3 N Lowest Force Peak = 0.2 N For liver, as low as 0.05 N http://www.mech.kuleuven.be/micro/pub/medic/Paper_Eurosenso s_2003_MIS_sensor_extended.pdf.
- 21. Force Limit Maximum Force measured to tear off beef 2.0 N ( 0.2N < 2.0N <2.3N) 2.0 N is set as a force limit and correspond to 2.9 Volt in the system.
- 22. Force Sensing Resistor How to measure force? VS FSR Strain Gauge • http://www.drrobot.com/products_item.asp?itemNumber=FSR400 • http://www.omega.com/literature/transactions/volume3/strain.html
- 23. Force Sensing Resistor Advantage: Cheaper Ideal for our system Advantage: Smaller in Size Disadvantage: Bigger than Semi- conductor S.G. FSR Disadvantage: Strain Changes without Gripping Strain Gauge
- 24. FSR Verification FSR 400 is used and currently the smallest fsr in the market Force (g) Resistance (kOhm) Day1 Day2 Day3 20 11.95 12 12 50 10 10.02 10 100 5.9 5.85 6 300 3.2 3.2 3.1 500 1.9 1.88 1.91 1000 1.2 1.2 1.22 2000 0.7 0.73 0.69
- 25. FSR Verification Resistance vs Force 0 2 4 6 8 10 12 14 0 200 400 600 800 1000 1200 Force (g) Resistance (kOhm) Day1 Day2 Day3
- 26. Transmitter and Receiver Transmitter Side: • Force on the gripper is compared with our limit force (2.9V) • Analog to digital conversion • Transfer signal serially to the receiver
- 27. Transmitter and Receiver Transmitter Side:
- 28. Transmitter and Receiver Receiver Side: • Transfer the received data to pc through serial port • Receives signal from transmitter when limit exceeds
- 29. Transmitter and Receiver Receiver Side:
- 30. Transmitter and Receiver Transmitter connected with tool
- 31. Transmitter and Receiver FSR attached on tool tip
- 32. Transmitter and Receiver Transmitter from top-view
- 33. Transmitter and Receiver Receiver with serial port connected
- 34. Alternative Design Option Without using RF module
- 35. Alternative Design Option Use PCB instead of Vector Board
- 36. Future Work - Hardware Use both FSR and Strain Gauge Research and experiment on real human tissue for setting force limit Varying force limit according to different surgery types PCB instead of vector board Research on smaller FSR or other components to measure force
- 37. Test Program – Moving Task Before moving task After moving task
- 38. Test Program – Cutting Task Before cutting task After cutting task
- 39. Test Program – Suturing Task Before suturing task After suturing task
- 40. Image Processing Final Solution : Colour Quantization Simple Effective
- 41. User Interface Simple Interface Main Control “The Green Arrow”
- 42. User Interface Task Selection Very Basic Controls
- 43. User Interface Task Mode
- 44. Evaluation Performance time – timer in the test program Gripping force – FSR sensor Accuracy – Image processing
- 45. Evaluation Quality > Speed
- 46. Problems Encountered Difficult Programming Language MFC Serial Data Collection FSR Sensor Data Image Processing Colours Complexity
- 47. Future Work - Software Modifying our test programs - providing random shape for cutting - various target locations for moving Add new test programs - Knot tying - Suction Add more feedback sensors - Checking tightness of suturing/tying task
- 48. Budget Component Cost SugiBox and surgical tools SFU Robotics Lab Computer SFU Robotics Lab Laparoscope SFU Robotics Lab Vector boards $24.00 Chip components $15.00 & SFU Robotics Lab CCD board camera $100.00 FSR sensors $30.59 Batteries and holders $23.84 Color paper, needle and tapes $15.00 Total $208.43
- 49. Market Plan Target market - Hospital - Medical school - Research Laboratory Provide an on-site training
- 50. Competitors Simulab Corporation Physical training system with digital camera (excluding PC) $1795.00 http://www.simulab.com/Laparosc opicSurgery.htm
- 51. Competitors Simulab Corporation LabTrainer Skill Set $225.00 http://www.simulab.com/Laparosc opicSurgery.htm
- 52. Cost and Selling Price Estimated Cost - Hardware (SurgiBox, camera, tools, surgical models, circuits, sensors) ~ $250 - Software (Test & Evaluation program) ~$200 Selling Price - Unit selling price of ~ $585 with 30% of margin - Much lower than Simulab Corporation products ($ 2020) - Providing both physical and virtual system product
- 53. Timeline - Project Schedule Gantt Chart Planned on January 2007
- 54. Timeline - Project Schedule Revised Schedule Planned on March 2007 - Project Completed by Apr.10th, 2007 Final Schedule on Project completion - Actual Project Completion on Apr.16th, 2007
- 55. Timeline - Project Schedule Main factors that caused delay - Hardware and software interface - Longer integration time than expected - Image processing complexity
- 56. Team Work Very Few Conflicts Good Communication Even Work Distribution Modulated Tasks Good Mix of Skill Sets Respect
- 57. What We Learned (Technical) Background knowledge in laparoscopic surgery - Research works in Dr. Payandeh’s Robotics Research Lab - CESEI Tour and meeting with Dr. Qayumi - Research from papers and webs Hardware - Microcontroller (PIC), RF transceiver, Voltage converter and Circuit design, PIC programming in Assembly Software - MFC - Serial port data reading in C++ - OpenCV and GDI+ Image Processing in C++
- 58. What We Learned (Team) Plan the whole project term Plan the project by month Plan the project by week Plan the project by day Go back up the ladder and make changes where necessary
- 59. Acknowledgements Supervisor SFU Robotics Lab Dr. Shahram Payandeh CESEI, Director Dr. Karim Quyami SFU Alumni Wayne Chan
- 60. The End Questions ?