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Laparoscopic Surgery Training System
MediTronics Inc.
CEO Alexander Hahn CTO Mark Jung CFO Han-Lim Lee
April 2007
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
Presentation Outline
• Background• Goals• Proposed Solution• System Overview• Hardware• Software • Business Case• Budget/Timeline• Conclusion
What’s Laparoscopic Surgery?
Minimally invasive surgery
Gas-inflated abdomen
Laparoscope and tools
Why Laparoscopic Surgery?
Small incision
Speed up recovery times
Minimize post-operative pain
Reduce the chances of infection
Minimize the size of scars
The Problems
Unusual surgery
environment
The Problems
Difficulty in use
of the tools
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
Goals
Providing an physical training system Providing an automated feedback &
evaluation system
A hybrid training system of physical and virtual feature
System Overview SurgiBox Computer
System Overview
Tools
System Overview FSR sensor
System Overview
Sensor feedback circuitry
System OverviewMoving task
System Overview Cutting task
System Overview Suturing task
Overall System
Hardware Outline
Hardware System Overview Force during surgeries FSR vs Strain Gauge FSR Verification Transmitter and Receiver Circuit Alternative Design Option Possible Future Work
H.W. System Overview
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.
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.
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
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
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
FSR VerificationResistance vs Force
0
2
4
6
8
10
12
14
0 200 400 600 800 1000 1200
Force (g)
Re
sis
tan
ce
(k
Oh
m)
Day1 Day2 Day3
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
Transmitter and Receiver Transmitter Side:
Transmitter and ReceiverReceiver Side:
• Transfer the received data to pc through serial port
• Receives signal from transmitter when limit exceeds
Transmitter and ReceiverReceiver Side:
Transmitter and Receiver Transmitter connected with tool
Transmitter and Receiver FSR attached on tool tip
Transmitter and Receiver Transmitter from top-view
Transmitter and ReceiverReceiver with serial port connected
Alternative Design Option
Without using RF module
Alternative Design Option
Use PCB instead of Vector Board
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
Test Program – Moving Task
Before moving task After moving task
Test Program – Cutting Task
Before cutting task After cutting task
Test Program – Suturing Task
Before suturing task After suturing task
Image Processing
Final Solution : Colour Quantization Simple Effective
User Interface
Simple Interface Main Control “The Green Arrow”
User Interface
Task Selection Very Basic Controls
User Interface
Task Mode
Evaluation
Performance time
– timer in the test program Gripping force
– FSR sensor Accuracy
– Image processing
Evaluation
Quality > Speed
Problems Encountered
Difficult Programming Language MFC
Serial Data Collection FSR Sensor Data
Image Processing Colours Complexity
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
Budget
Component CostSugiBox 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
Market Plan
Target market
- Hospital
- Medical school
- Research Laboratory Provide an on-site training
Competitors
Simulab Corporation Physical training
system with digital camera (excluding PC)
$1795.00
http://www.simulab.com/LaparoscopicSurgery.htm
Competitors
Simulab Corporation LabTrainer Skill Set $225.00
http://www.simulab.com/LaparoscopicSurgery.htm
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
Timeline - Project ScheduleGantt Chart Planned on January 2007
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
Timeline - Project Schedule
Main factors that caused delay
- Hardware and software interface
- Longer integration time than expected
- Image processing complexity
Team Work
Very Few Conflicts Good Communication Even Work Distribution Modulated Tasks Good Mix of Skill Sets Respect
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++
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
Acknowledgements
Supervisor SFU Robotics Lab Dr. Shahram Payandeh
CESEI, Director Dr. Karim Quyami
SFU Alumni Wayne Chan
The End
Questions ?