h. adldoost s.j. fattahi project of mems course supervisor: dr.zabihollah 1 sharif university of...
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Multisensing Minimaly Invasive Surgery
H. Adldoost S.J. Fattahi
Project of MEMS CourseSupervisor: Dr.Zabihollah
Sharif University of Technology, Int’l Campus, 2010
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Outlines
• Introduction
Invasive surgery Advantage
Invasive surgery Problems
• Gripper + Camera• Motivation for MIS• Why flexible tactile sensor ?• Sensing Using FBG• Shear Sensing Using ZnO• Final proposed Structure• Modeling
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Invasive surgery Advantage
•less pain, less strain of the organism •faster recovery
•small injuries (aesthetic reasons) •economic gain (shorter illness time)
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Invasive surgery Problems
•Restricted vision
•Difficult handling of the instruments
•Very restricted mobility
•Difficult hand-eye coordination
•No tactile perception
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Gripper + Camera(Conventional System)
Outside bodyInside body
Minimally Invasive Surgery (MIS, in german: MIC) performed by the help of: 1- small endoscopic camera
2-several long, thin, rigid instruments (Grippers, Graspers, Cutter and….
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Motivation for MIS
Haptic information Tactile sensor
Microsurgery
Actuator
Robotics
Pulsating system
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Why flexible tactile sensor ?
Increased reach, more accurate surgery Miniaturized surgical tool
Smaller space for sensors Not plane (arbitrary) surface !!
Silicon supporting structure
Zno with Polysilicon Cover
Diaphragm
Thin diaphragm structure
Silicon substrate
Zno Passivation
Oxide
Air gap Poly-Si
Capacitive type Structure
Silicon substrate Bulk Sensing material: Polysilicon Rather complex process Mechanically not stable Bulk micromachining Time consuming work
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Sensing Using FBG
Wavelength signal will be reflected coherently to make a large reflection.
r = 2neff
in
Reflection spectrum
reflect
Transmission spectrum
trans.
n (refraction index difference)
where neff is the effective refractive index of the mode propagating in the fiber and is the FBG period
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Temperature SensingUsing FBG
B = B (1 - ) + B( + )T
FBG sensors are sensitive temperature by:
, , and are respectively the photoelastic, thermal expansion and thermo-optic .
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Temperature SensingUsing FBG
0 0.13 0.63000000000000
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1.13 1.63 2.13 2.63 3.13 3.63 4.13 4.63 5.13 5.63 6.13 6.63 7.13 7.63 8.13 8.63 9.13 9.63
Temperature
0 1.313
6.36299999999999
11.413
16.4629999999999
21.513
26.563
31.613
36.663
41.713
46.763
51.813
56.863
61.913
66.963
72.013
77.063
82.113
87.163
92.213
97.263
10.00
30.00
50.00
70.00
90.00
110.00
ΔλB/ΔT = 10.1 pm/◦C
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X-Y Strain SensingUsing FBG
x = x (1 - ) + B( + )T
FBG sensors are sensitive temperature by:
y = y (1 - ) + B( + )T
Normal stress in FBG under diametrical loading
E: 69 GPan0 = 1.45ν = 0.29p11 = 0.121p12 = 0.270Fiber diameter = 125 microns
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Normal stress in FBG via FEA
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Bragg Wavelength change
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Shear Sensing
Polyimide substrate
Polyimide passivation
Bottom electrode (Cr/Au)
Top electrode (Al)
Silicon dioxide
Sensing layer (ZnO)
Polyimide substrate and passivation layer Flexibility Sensing material: ZnO Simpler fabrication process
Mechanically more stable Only with surface micromachining
ZnO sensing layer No thermal problems and additional
thermal poling process such as PZT or PVDF
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Fabrication Steps
Silicon wafer
(a) Polyimide spincoating and curing
(b) Bottom electrode deposition and patterning
(c) Silicon dioxide deposition and patterning
(d) ZnO layer deposition and patterning
(e) Silicon dioxide deposition and patterning
(f) Top electrode deposition and patterning
(g) Polyimide passivation layer spincoating and patterning
(h) Etch-release
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Electro Mechanical Coupling of ZnO
E=Electric fieldD=Electric displacementϵ=PermittivityT=Thicknessd= strain coefficient
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Finding Rate of Normal and Shear Stain using a ZnO
33 Mode:
31 Mode:
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Viscous Material Complience Matrix
Above stress/strain-rate relationship may be obtained for the flow of a viscous Material
where : σ is the stress ἐ the extensional strain-rateγ the shear-rate components
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Final Gripper Structure
Zno
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Modeling
Elements used are:PLANE 82 for the grasper jawPLANE 223 for ZnO layerPLANE 42 for FBGPLANE 85 for fixture plate of ZnO
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ANSYS Model
Gripping an object gripper
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ANSYS Model
• Force Applied • Deformation
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References
• J. Dean Callaghan, and M. Mark McGrath, “A Force Measurement Evaluation Tool for Telerobotic Cutting Applications: Development of an Effective Characterization Platform”, International Journal of Mathematical, Physical and Engineering Sciences, vol 1, no 3, August 2007.
• S. Sokhanvar, M. Packirisamy and J. Dargahi, “A multifunctional PVDF-based tactile sensor for minimally invasive surgery”, Smart Mater. Struct. Vol.16, 2007, 989–998.
• M. Shikida, T. Shimizu, K. Sato and K. Itoigawa, “Active tactile sensor for detecting contact force and hardness of an object”, Sensors Actuators, 2003, Vol. 103 213–8.
• Anindya Ghoshal, Mannur J. Sundaresan, Mark J. Schulz, P. Frank Pai, “Structural health monitoring techniques for wind turbine blades”, Journal of Wind Engineering and Industrial Aerodynamics 85 (2000) 309-324.
• [Kyungmok Kim, Jong Min Lee, Yoha Hwang, “ Determination of engineering strain distribution in a rotor blade with fiber Bragg grating array and a rotary optic coupler”, Optics and Lasers in Engineering 46 (2008) 758– 762.
• M. Tanimoto, F. Arai, T. Fukuda, H. Iwata, K. Itoigawa, Y. Gotoh,M. Hashimoto, and M. Negoro, “Micro force sensor for intravascular neurosurgery and in vivo experiment,” Proc. IEEE Int. Workshop Micro Electro Mechanical Systems (MEMS 98), pp. 504–509.
• [21] H. Takizawa, H. Tosaka, R. Ohta, S. Kaneko, and Y. Ueda, “Development of a microfine active bending catheter equipped with MIF tactile sensors,” Proc. 12th IEEE Int. Conf. Micro Electro Mechanical Systems (MEMS’99), pp. 412–417.
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Thank You