Title :
Investigating protein structure with a microrobotic system
Author :
Sun, Yu ; Greminger, Michael A. ; Nelson, Bradley J.
Author_Institution :
Swiss Fed. Inst. of Technol., Zurich, Switzerland
fDate :
26 April-1 May 2004
Abstract :
This paper presents a microrobotic system integrating microscope vision and microforce feedback for characterizing biomembrane mechanical properties. Robust visual tracking of deformable biomembrane contour using physics-based models is described. A multi-axis MEMS-based force sensor is used to determine applied forces on biomembranes and develop a novel biomembrane mechanical model. By visually extracting geometry changes on a biomembrane during loading, geometry changes can be used to estimate applied forces using the biomembrane mechanical model and the determined elastic modulus. Forces on a biomembrane can be visually observed and controlled, thus creating a framework for vision and force assimilated cell manipulation. The experimental results quantitatively describe mouse zona pellucida (ZP) stiffness increase during ZP hardening and provide an understanding of ZP protein structure development, i.e., an increase in the number of cross links of protein ZP1 between ZP2-ZP3 units that is conjectured to be responsible for ZP stiffness increase. Furthermore, the system, technique, and model presented in this paper can be applied to investigating mechanical properties of other biomembranes and other cell types, which has the potential to facilitate many biological studies, such as cell injury and recovery where biomembrane mechanical property changes need to be monitored.
Keywords :
biomembranes; computerised monitoring; condition monitoring; elastic moduli; feedback; medical robotics; microrobots; physiological models; proteins; robot vision; ZP protein structure development; biomembrane mechanical properties; elastic modulus; microforce feedback; microrobotic system; microscope vision; mouse zona pellucida stiffness; multiaxis MEMS-based force sensor; protein structure investigation; robust visual tracking; Biomembranes; Cells (biology); Deformable models; Feedback; Geometry; Machine vision; Mechanical factors; Microscopy; Protein engineering; Robustness;
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8232-3
DOI :
10.1109/ROBOT.2004.1307493