Abstract We present a real-time haptics-aided injection technique for biological cells using miniature compliant mechanisms. Our system consists of a haptic robot operated by a human hand, an XYZ stage for micro-positioning, a camera for image capture, and a polydimethylsiloxane (PDMS) miniature compliant device that serves the dual purpose of an injecting tool and a force-sensor. In contrast to existing haptics-based micromanipulation techniques where an external force sensor is used, we use visually captured displacements of the compliant mechanism to compute the applied and reaction forces. The human hand can feel the magnified manipulation force through the haptic device in real-time while the motion of the human hand is replicated on the mechanism side. The images are captured using a camera at the rate of 30 frames per second for extracting the displacement data. This is used to compute the forces at the rate of 30 Hz. The force computed in this manner is sent at the rate of 1000 Hz to ensure stable haptic interaction. The haptic cell-manipulation system was tested by injecting into a zebrafish egg cell after validating the technique at a size larger than that of the cell

G K Ananthasuresh

V Mallikarjuna Rao

CiteSeerX

14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009-RVM6 
  181
Haptic Feedback for Injecting Biological Cells  
using Miniature Compliant Mechanisms 
 
V. Mallikarjuna Rao and G.K. Ananthasuresh* 
Department of Mechanical Engineering, Indian Institute of Science, Bangalore, India 
 
{malli, suresh}@mecheng.iisc.ernet.in) 
* Corresponding author 
 
 
Abstract 
We present a real-time haptics-aided injection technique 
for biological cells using miniature compliant mechan-
isms.  Our system consists of a haptic robot operated by 
a human hand, an XYZ stage for micro-positioning, a 
camera for image capture, and a polydimethylsiloxane 
(PDMS) miniature compliant device that serves the dual 
purpose of an injecting tool and a force-sensor. In con-
trast to existing haptics-based micromanipulation tech-
niques where an external force sensor is used, we use 
visually captured displacements of the compliant me-
chanism to compute the applied and reaction forces. The 
human hand can feel the magnified manipulation force 
through the haptic device in real-time while the motion 
of the human hand is replicated on the mechanism side. 
The images are captured using a camera at the rate of 30 
frames per second for extracting the displacement data. 
This is used to compute the forces at the rate of 30 
Hz.  The force computed in this manner is sent at the 
rate of 1000 Hz to ensure stable haptic interaction. The 
haptic cell-manipulation system was tested by injecting 
into a zebrafish egg cell after validating the technique at 
a size larger than that of the cell. 
Keywords: cell-manipulation, remote-haptics, vision-
based force sensing, and intracytoplasmic injection. 
1 Introduction 
Haptic feedback or simply “haptics” is the use of sense 
of touch in a user-interface to provide force information 
to a user [1]. Although it has been widely used in virtual 
reality applications [2, 3] such as medical simulation and 
virtual painting, it has also been effectively applied in 
tele-manipulation systems for interaction between a 
slave robot and real deformable object [4-6]. Currently, 
the reaction force between a remote tool (injecting pi-
pette) and a real object (biological cell) is measured ei-
ther by using external force transducer or by using visual 
data of the deformed real object [7-10]. However, these 
methods have some difficulties such as real-time signal 
processing, increased system complexity, and inability 
in accurate modeling of the unknown properties of the 
real object, which in our case is a biological cell. 
 Haptic feedback enables evaluation of human fac-
tors in performing the cell-injection. The success rate of 
manual injection technique is very low, which is attri-
buted to the lack of force feedback [9] when knobs or 
joystick of injection tools are operated by the user. 
When injecting into the nucleus of an egg cell, it is im-
portant not to inject into the cytoplasm. Hence, the user 
should know when the cell-membrane is pierced and 
then when the nuclear membrane is penetrated. Visual 
information is often not enough and thus warrants the 
force feedback. In [7], this was done using a polyvinyli-
dene fluoride (PVDF) sensor and a haptic interface. Our 
work is along the similar lines but with a difference: we 
do not use an external force sensor; our injecting tool 
itself doubles up as a force sensor.  
 Thus, this study entails a cell injection algorithm 
with haptic feedback (see Fig. 1) based on real-time vis-
ual data of the displacement-amplifying compliant me-
chanism (DaCM) which is used as a force sensor. Since 
both the visual information and a force sensor (DaCM) 
are used, we can get the combined advantages and over-
come the limitations of both the methods. In order to 
provide force feedback, a customized image processing 
algorithm is used to track the displacement measuring 
edge of the DaCM and thereby estimate the reaction 
force based on visual information. These estimated 
forces computed at 30 Hz rate are sent at 1000 Hz up-
date rate for stable haptic feedback. This means that the 
transmitted haptic force is updated every 1/30th of a 
second. 
 
Fig. 1: Conceptual diagram of the cell-injection system 
with haptic feedback using a displacement-amplifying 
compliant mechanism (DaCM). 
2  Methodology 
14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009- RMV6 
  182
The cell injection system shown in Fig. 2, comprises a 
3-DOF XYZ micro-positioning tool (also called a micro-
robot, MP-285, Sutter Inc.), a syringe (SGE Analytical 
Science) with a tube and pipette attached for holding a 
cell, an inverted microscope with 2-DOF motorized po-
sitioning stage (IX71, Olympus Inc.), a charge coupled 
device (CCD) camera (SSC-DC54AP, Sony Inc.), and a 
complementary metal oxide semiconductor (CMOS) 
camera (SC-08, Smart Infocomm Pvt. Ltd.) for vision 
based force-sensing. We use a displacement-amplifying 
compliant mechanism (DaCM) made in-house with po-
lydimethylsiloxane (PDMS) to measure the cell injec-
tion forces. The PDMS material is suitable for our appli-
cation because of its high compliance and good sensitiv-
ity with our force-sensing technique. The glass micropi-
pette is attached to the DaCM using a strong adhesive to 
realize a firm joint. The DaCM and the CMOS camera 
are attached to a custom-made holder which intern is 
attached to the micro-positioning stage (MP-285) so that 
the whole arrangement forms the cell injecting unit. The 
micro-robot motion is controlled by a human user 
through a haptic device (PHANTOM Premium 
1.5/6DOF HF, SensAble Technologies Inc.) and a PC 
controller. The cell injection forces measured using the 
vision feedback are magnified and are transmitted to the 
user through the haptic device. 
 The block diagram for the cell-injection system is 
shown in Fig. 3. It consists of four loops: haptic loop, 
micro-robot loop, video loop, and computation loop. 
The haptic loop helps fetch the position of the haptic 
device to the personal computer (PC) and sending the 
calculated force to the user in real-time. The micro-robot 
loop sends the current position from the PC to the mi-
cro-robot in real-time so that the user’s motion is repli-
cated on the DaCM side of injection system. The video 
loop manages to get the video data from the cameras to 
the PC and then to the display system in real-time. The 
computation loop performs the image processing to cal-
culate the reaction forces in real-time.  
2.1 Design and Calibration of the Force 
Sensor (DaCM) 
A displacement-amplifying compliant mechanism 
(DaCM) uses the input force applied at one point (input 
point) to give an amplified displacement at another point 
(output point). The DaCM was designed based on the 
methods developed in [11, 12]. Topology, size and shape 
optimization were used to design the DaCM (see Figs. 
4(a-b)). Figure 4(a) shows the geometric model of the 
mechanism with dimensions, and Fig. 4(b) shows the 
prototype fabricated in-house using polydimethylsilox-
ane (PDMS) material using wire-cut electro discharge 
machined (EDM) aluminium mould and vacuum-casting.  
 The objective function maximized in topology op-
timization was the ratio of the displacements at the out-
put and input points subjected to equilibrium equations,  
 
Fig. 2: Experimental setup for cell injection. 
 
Fig. 3: Block diagram of the cell injection system. 
a volume constraint, and upper and lower bounds on the 
design variables. After obtaining the basic topology from 
topology optimization, the size and shape optimization 
was done by keeping in mind the fabrication constraints 
and the high unloaded output displacement [11]. The 
objective function for size and shape optimization was 
the same as the objective function of topology optimiza-
tion, but the design variables here were the length, orien-
tation and the width of the features of the basic topology. 
This two-stage optimization helps in getting a design that 
obeys the manufacturing constraints of wire-cut Eelectro 
Discharge Machining (EDM). 
14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009- RMV6 
  183
 Nonlinear large displacement finite element analysis 
(FEA) was done, using COMSOL MultiPhysics finite 
element software on the DaCM to calibrate it theoreti-
cally. A set of forces ranging from 0 to 1500 Nµ  in 
steps of 50 Nµ  was applied on the DaCM input point 
and the displacement of the output point was calculated. 
The force vs. displacement plot is shown in Fig. 5. This 
data is used to find out the force value from the dis-
placement value in real-time. The real model of the force 
sensor (i.e., DaCM) tends to show local buckling when 
the output displacement exceeds 1 mm. Therefore, the 
maximum force that can be measured is 1200 Nµ , 
which is adequate in the cell-injection task. 
 
(a)  
(b)  
 
Fig. 4: (a) Topology, shape and size optimized dis-
placement-amplifying compliant mechanism (DaCM), 
(b) manufactured prototype using polydimethylsiloxane 
(PDMS) by vacuum casting with a wire-cut aluminium 
mould. All dimensions in (a) are in mm. 
2.2 Vision-based Force-sensing 
The displacement of the output point is measured in 
terms of the number of pixels of the image in real-time 
by using a customized edge-detection algorithm. This 
pixel displacement is mapped to find the absolute dis-
placement and then to find the reaction force (see Fig. 6). 
The reaction force computed in this manner is updated at 
a rate of 30 Hz. But for stable haptic rendering, we need 
the force update rate to at 1000 Hz. To achieve this re-
quirement, we use a step-wise interpolation. That is, we 
use the force computed at the time of previous graphic 
update for all the haptic updates until the new graphic 
update of force is done. This means, we use the same 
force computed at 0 ms (first graphic update) for the 
haptic updates of 0, 1, 2, 3 … 34 ms (first to 35th update). 
 With the camera and the setup used, 3 mm of abso-
lute length takes 100 pixels length (i.e., 0.03 mm/pixel). 
The edge-detection algorithm gives a noise of one pixel 
because of the variation in image quality from frame to 
frame. Therefore, the least measurable distance in pixels 
is two and hence it is 0.06 mm. Consequently, from the 
force vs. displacement data of the force sensor, the least 
measurable force is approximately 50 Nµ .  
 
Fig. 5: Force vs. Displacement plot for the force sensor 
(DaCM). 
 
Fig. 6: Block diagram of vision based force sensing. 
 
14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009- RMV6 
  184
3  Results 
We first validated our method and the setup by working 
with an object that is much larger than an egg cell of 
zebrafish and for which there is an independent way to 
verify the measured force. For this, we chose a spring 
steel cantilever of 25 mm × 10 mm × 0.2 mm size and 
set up a test-bed without using the microscope. Since the 
size of this is large, we used a larger DaCM than the one 
shown in Fig. 4b for measuring the force. This was made 
using spring steel on a wire-cut EDM. The setup is 
shown in Figs. 7(a-b). Figure 7(a) shows the cantilever 
undeformed because the probe tip of the DaCM is not 
touching it whereas in Fig. 7(b), we can see that it has 
deflected. The DaCM was actuated by the XYZ stage 
(MP 285) as per the hand-movement of the user holding 
the haptic device. We verified the force estimated by the 
DaCM agreed with that given by the deflection formula 
of the cantilever. 
 (a)  
(b)  
Fig. 7: Macro-scale experiment for validating the remote 
haptics technique with a spring-steel cantilever. (a) just 
before touching, (b) after deformation. 
 We then performed experiments (see Fig. 8), on 
zebrafish egg cells to test our injection system. The in-
jecting pipette with the holding arrangement is moved by 
a user through the haptic device and the forces expe-
rienced by the injecting pipette are felt by the user 
through the same haptic device. A scaling factor of 1/30 
is used for the distance-mapping and 10,000 for force-
mapping between macro and micro environments; this 
means that when the user moves the haptic device probe 
by 30 units of distance, the micro-robot and holder ar-
rangement moves by one unit; and when the actual force 
is one unit, the user feels 10,000 units of force through 
the haptic device. The plot of the measured force vs. the 
displacement of the micro-positioning stage is shown in 
Fig. 9. Since the egg cell was taken from zebrafish at the 
early stage of its cell growth, they were very soft and 
resulted in a maximum measured force of 100 Nµ only. 
 The experiment described above demonstrated cell-
injection but it damaged the cell as can be seen in the E 
and F stages of Fig. 8. However, it confirms the effec-
tiveness of our method. The reason for damage of the 
cell was not a consequence of the methodology; it was 
simply because the diameter of the needle used was quite 
large. When we used a fine needle (see Fig. 10), we were 
able to gently penetrate the cell. But we could not inject 
with it due to the lack of a pump that can provide the 
pressure needed for injection through a fine needle. Pro-
curing a peristaltic pump and performing successful in-
jection and extensive experimentation are currently in 
progress. 
 
 
Fig. 8: An example of zebra fish cell injection using 
compliant mechanism as a force sensor and injector with 
haptic feedback. 
(A) Injecting pipette is approaching the cell. 
(B) Injecting pipette touched the cell. 
(C) Cell is deformed. 
(D) Injecting pipette is still moved forward by user. 
(E) Cell membrane is punctured. 
(F) Inner contents of the cell are coming out. 
 
14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009- RMV6 
  185
 
Fig. 9: Plot of measured force vs. distance moved by 
micro-positioning stage. (A) to (F) are the stages of 
Fig. 8.  
 
Fig. 10: A zebra fish egg cell pierced gently using a fine 
needle. 
4 Closure 
We demonstrated the real-time cell injection with haptic 
feedback. A novel method of force-sensing is used with 
haptics. Using this setup, the cell injection can be done 
more effectively as it provides visual and force feedback 
in real time. Systematic evaluation of the success rate 
using extensive testing and adding haptic feedback for 
cell-grasping are part of our ongoing work. The motiva-
tion for the latter is that vacuum-gripping using pipettes 
(as was done in this and other works) could potentially 
damage the cell. Our rationale for using a compliant me-
chanism for force-sensing (as opposed to an external 
force sensor) is that the same can also be used for grasp-
ing and thus provide force-feedback in grasping delicate 
and flexible objects such as the cells and embryos. 
Acknowledgments 
The authors would like to thank Ramu, Vinod and Ravi 
for their help in fabrication of grippers. This work is 
supported in part by the Swarnajayanthi fellowship of 
the Department of Science and Technology (DST), 
Government of India, to the second author as well as the 
Math Biology grant from DST. 
 
References 
 [1] Mandayam, A.S., and Basdogan, C., “Haptics in 
Virtual Environments: Taxonomy, Research Status, and 
Challenges,” Computers and Graphics, Vol. 21, No. 4, 
1997, pp.393-404. 
 
[2] Salisbury, J.K., and Mandayam, A.S., “Phantom-
Based Haptic Interaction with Virtual Objects,” IEEE 
Computer Graphics and Applications, Vol. 17, No. 5, 
1997, pp.6-10. 
 
[3] Vivek, N.H., “Interactive Haptic Rendering,” Mas-
ter of Engineering Project Report, Department of Me-
chanical Engineering, Indian Institute of Science, 2007. 
 
[4] J. Park and O. Khatib, “A haptic teleoperation ap-
proach based on contact force control,” International 
Journal of Robotics Research, vol. 25, 2006, pp. 575-
591. 
 
[5] Basdogan, C., De, S., Kim, J., Muniyandi, M., Kim, 
H., and Mandyam, A.S., “Haptics in minimally invasive 
surgical simulation and training,” IEEE Computer 
Graphics and Applications (IEEE CG&A), March/April 
2004, pp.56-64. 
 
[6] Okamura, A.M., “Methods for haptic feedback in 
teleoperated robot-assisted surgery,” Industrial Robot: 
An International Journal, Vol. 31, No. 6, 2004, pp. 499-
508. 
 
[7] Pillarisetti, A., Pekarev, M., Brooks, A.D., and 
Desai, J.P., “Evaluating the Effect of Force Feedback in 
Cell Injection,” IEEE Transactions on Automation 
Science and Engineering, vol. 4(3), 2007, pp. 322-331. 
 
[8] Jungsik Kim, Youngjin Kim, and Jung Kim, 
“Real-time haptic rendering of slowly deformable bo-
dies based on two dimensional visual information for 
telemanipulation,” International Conference on Control, 
Automation, and Systems, October 17-20, 2007, 
pp.2448-2451. 
 
[9] Yu, S. and Nelson, B.L., “Autonomous Injection of 
Biological Cells using Visual Servoing,” in Experimen-
tal Robotics VIII, LNCIS 271, D. T\Rus and S. Singh 
(eds.), 2001, pp. 169-178. 
 
[10] Wang, W., Liu, X., Gelinas, D., Ciruna, B., and Sun, 
Yu, “A Fully Automated Robotic System for Microin-
jection of Zebrafish Embryos,” PLoS ONE, 
www.plosone.org, Sep. 2007, Issue 9, e862. 
 
[11] Sahu, D.K., “Topology Optimization and Prototyp-
ing of Miniature Complaint Grippers for Micromanipu-
lation,” Master of Engineering Project Report, Depart-
ment of Mechanical Engineering, Indian Institute of 
Science, 2008. 
14th National Conference on Machines and Mechanisms (NaCoMM09), 
NIT, Durgapur, India, December 17-18, 2009  NaCoMM-2009- RMV6 
  186
[12] Krishnan, G. and Ananthasuresh, G. K., “A Sys-
tematic Method for the Objective Evaluation and Selec-
tion of Compliant Displacement Amplifying Mechanisms 
for Sensor Applications,” Journal of Mechanical Design, 
Volume 130,  Issue 10, 2008, pp. 102304:1-9. 
 
 
 


Haptic Feedback for Injecting Biological Cells using Miniature Compliant Mechanisms

http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=C61B4E93F3072C738FDD1688D5255D08?doi=10.1.1.1054.3280&rep=rep1&type=pdf

Haptic Feedback for Injecting Biological Cells using Miniature Compliant Mechanisms

Abstract

Similar works

Full text

Available Versions

CiteSeerX