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

6. The Problems Unusual surgery environment

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

10. System Overview SurgiBox Computer

11. System Overview Tools

12. System Overview FSR sensor

13. System Overview Sensor feedback circuitry

14. System Overview Moving task

15. System Overview Cutting task

16. System Overview Suturing task

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

19. H.W. System Overview

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) Day1Day2Day3 2011.9512 501010.0210 1005.95.856 3003.2 3.1 5001.91.881.91 10001.2 1.22 20000.70.730.69

25. FSR Verification

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 ComponentCost SugiBox and surgical toolsSFU Robotics Lab ComputerSFU Robotics Lab LaparoscopeSFU 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.10 th, 2007 Final Schedule on Project completion - Actual Project Completion on Apr.16 th, 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 ?