robotics for biological and medical applications€¦ · robotics for biological and medical...

World Technology Evaluation CenterInternational Study of Robotics Research

Robotics for biological and medical applications study group:

Yuan F. Zheng, The Ohio State University (Presenter)George Bekey, University of Southern California

Art Sanderson, RPI

Robotics for Biological and Medical Applications

World Technology Evaluation CenterInternational Study of Robotics Research--Supported by NASA, NSF and NIH 2

What?Robotics and automation technologies used in biological and medical applications

Cell manipulation –DNA deposition –

Univ. Minn, ETH-Zürich

Stereotactic brain surgery

High throughput sample processor (DNA, protein

crystallography, etc.) – U. of Washington


Why robots and automation in biology and medicine (1)?

Biology- high throughput for experiments related to life science

drug discoveryprotein crystallizationDNA sequencing

- micro-manipulation, and micro-handling of bio-samplescell, blood, sputum, gynecological, colorectal

- efficient production and analysis of DNA and protein micro-arrays- functional analysis of living cells- automated protein crystallography- effective exploration of molecular and cell biology

Off-shell Micro-actuator


Why robots and automation in biology and medicine (2)?

Medicine- non-invasive surgeries and diagnosis- precision and repeatability of robots means

consistency and quality- targeted delivery of drugs- robotic prosthetic legs and arms with intelligence

Pillcam - providing images of esophagus


Robotic tools, devices and systems- general purpose robotic devices and systems- special purpose robotic devices and systems- sensors

- visual sensing- force sensing- neuro-sensing

- image processing

Micro-force sensor using IC fabrication technology - - Univ. Minn, ETH-Zürich

Implantable electrode for neuron-signal detection - Polo

Sant’Anna Valdera of Sant’Anna School of Advanced Studies


Key technologies- MEMS (IC-based micro-fabrication, conventional micro-machining)

- SensingMicroscopes, AFMCapacitive measurements

- ActuationPiezoelectric, Electrostatic, Electromagnetic, Molecular

- Miniature tools and devices for handling bio-samples- analysis and predictive algorithms for bio-applications- analysis and modeling algorithms for surgery- human-machine interface in robotic surgery - system integration for automation in life science- solid understanding of life science and human body

Protein folding modeling

Patient-specific modeling for robotic surgery


Example 1: Automated cell injection for pronuclei DNA injection using visual servoing

• Demonstrated for the first time by Sun and Brad Nelson(Univ. Minn, ETH-Zürich)


Example 2: High throughput for life science research

• High-throughput robotics and automation systems to prepare bio-samples (DNA, protein crystallography, and so on) - Deirdre Meldrum at U. of Washington (pictures shown earlier)

• High-throughput robotic systems for large-scale DNA sequencing, SNP analysis, and haplotype mapping - Eric Lander at the Broad Institute (MIT, Harvard, Whitehead Institute)

• High-throughput screening robot to test 1 million compounds a day -Novartis Research Foundation’s Genomics Institute

• High-throughput preparation of bio-samples of high viscosity for membrane protein crystallization - Y. F. Zheng at The Ohio State University

Kalypsys robotic system developed at

Novartis


Example 3: Robotic cell-handling

1. Nagoya U. Approach– a novel separation method for random screening

of target cells from a large heterogeneous population using a local photo polymerization

– photo-crosslinkable resin and local irradiation of UV light from mercury lamp for cell immobilization

– succeeded in single cell immobilization and basic experiments such as culture and fluorescent dyeing of immobilized cells

2. Non-contact manipulation (laser trapping) of multiple cells - Fumi Arai, etc. (Nagoya University)

3. Electroactive polymer cell manipulation - Wen J. Li (Chinese University of Hong Kong)

4. Automated cell handling - Sun, Nelson (Univ. Minn, ETH-Zürich) Nagoya non-contact cell trapping


Example 4: Robotic surgery


Example 5: Robotic microsurgery

Robotic microsurgery-Scaling (JPL)


Example 6: Robotically assisted lung biopsy

Robotic system automatically takes lung biopsy sample under CT fluoroscopy

-K. Cleary (Georgetown)-R. Taylor (Johns Hopkins-C. White (Maryland)


Fundamental Research Challenges (1)

In Biology • Research challenges in general

– Engineers with limited knowledge of life science and medicine

– Lack of effective tooling and sensing technologies to deal with massive and tiny bio-materials and bio-samples

– New developments in devices and systems are evolutional not revolutionary

• Research challenges in particular– Automated cell handling and operations (probing and

sensing)– Automated protein characterization and functional analysis– Automated protein crystallography - crystallization,

harvesting, x-ray detection– Automated DNA sequencing (still slow)– Automated DNA and protein chip production and analysis


Fundamental Research Challenges (2)

In Medicine (by Russ Taylor):

• Modeling and analysis: computationally effective methods for patient-specific modeling and analysis.

• Interface technologies: extension of the sensory, motor, and human-adaptation abilities of computer-based systems in a demanding and constrained environment.

• Systems: architectures, building blocks and analysis techniques facilitating rapid development and validation of versatile CIS systems and processes with predicable performance.

Master-slave device with stiffness control – Keio University, Japan


Challenging Example (1): Protein Crystal Harvesting

Pieces of protein crystals (pink)Automated picking-up and mounting to the loop for x-ray crystal-graphics

Protein crystal is too small to handle automatically- 3D vision for tiny space is challenging- Picking and placing by machine is extremely difficult if not impossible


Challenging Example (2): Capsular Endoscope

• Application: diagnosis and therapy of gastrointestinal tract of human beings

• Robotic device: an active device which can automatically move in a tubular, compliant and slippery environment

• Need advanced MEMS, electronics, sensing, data storage, communications, autonomous, control, etc. technologies.

• Several devices have been developed including the one by Polo Sant’Anna Valdera of the Sant’Anna School of Advanced Studies, Italy http://www-crim.sssup.it/research/projects/Emiloc/emiloc.html


Challenging Example (3): Robotic knee replacement surgery

Architectures, building blocks and analysis techniques facilitating rapid development and validation of CIS systems and processes (Johns Hopkins U.)


Regions Visited by the Assessment Team

U.S. Workshop Presentations- U. of Washington, Johns Hopkins, U. of Minnesota-OSU

Japan - Nagoya University, Wasada University, ATR Computational Neuroscience Laboratories

Korea- KIST, Seoul National University

Europe- ETH-Zürich, Polo Sant’Anna Valdera of the Sant’Anna School of Advanced Studies (Italy), University of Zurich Artificial Intelligence Laboratory



U.S. Examples (1)

• U. of Washington• Johns Hopkins University• U. of Minnesota• Standford University• The Ohio State University• Columbia University• U. of Southern California• Duke University• Harvard University• Etc. Ohio State visual

guided protein harvesting system

Automated Multiplex OligonucleotideSynthesizer (AMOS), 96/3.5 hours


U.S. Examples (2)

Microsystems for real-time measurements of single live cells

- Deirdre Meldrum, U. of Washington

Robotic theory for protein folding- Nancy Amato, Texas A&M- Jean-Claude Latombe, Stanford


U.S. Examples (3)

Digital optical chemistry systemfor micro-array production

- Harold (Skip) Garner at the U. of Texas SW Medical Center

Robotic surgical systems- Russ Taylor, Johns Hopkins U.


Asia Examples (1)

Non-contact cell manipulation- Nagoya University (Japan)

Artifacts resulting from research in intravascular surgery: 3D-reconstructed cerebral arterial model based on CT images and an in vitro model of human aorta.

CT slice image

Vertical image

Reconstructed 3D arterial structure with BT (basilar top) aneurysm

Intravascular surgery-Nagoya University (Japan)


Asia Examples (2)

• ATR Computational Neuroscience Laboratories (Japan)– understanding the brain function using a computational approach,” i.e.,

“understanding the brain by creating one.”• Wasada University (Japan)

– Robotic surgery• Seoul National University (Korea)

– Nano and MEMS for bio-applications• KIST (Korea)

– Cell Handling

A thermally actuated micro gripper for manipulating micro objects ranging from 10 to 500µm such as fish eggs – Chinese U. of Hong Kong – W. J. Li


Study the mechanical properties of the cell embryo

• ETH Swiss Federal Institute of Technology, Zurich, Institute for Robotics and Intelligent Systems (IRIS)

A Probe Station with two micro manipulators and a microscope for biological cell handling

Europe Examples (1)

Micro-robotics and biomicrorobotics


Europe Examples (2)• University of Zurich Artificial Intelligence Laboratory Dept. of

Information Technology– Evolution of artificial cells: the study of the evolution of cells to mimic

biological growth• Polo Sant’Anna Valdera of the Sant’Anna School of Advanced

Studies, Italy– Micro-devices for bio-sensing such as implantable sensing devices

Capsular Endoscope• University of Genova (Italy)

– Haptic control– Human-eye control

Robotic eyes studying human-muscle control- University of Genova


Quantitative Observation

• U.S. is leading the world in the numbers of research groups and areas of the research– Hard to dispute at this time

• Many U.S. universities are extremely active in biology research• U.S. industry is more aggressive in commercialization• Produce the demands for robotics and automation for life science

• More countries are joining the group– Quality is also rising (the best paper in cell-handling in ICRA2003

is from Hong Kong)– Some are ahead of U.S. (such as cell handling)


Qualitative Observation

• For biological applications– Research on robotics and automation in bio-applications is young– Research quality in the U.S. is as good as that in Asia and Europe– Research results vary from laboratory demonstrations to reliable

applications in industry– Research approaches are Ad Hoc (no systematic theory)– Applications heavily rely on the progress of nano and MEMS

technologies– Collaboration between engineering and biology is challenging

• For medical applications– Robotics surgery is leading the world for heart, brain, knee, spinal

cord operations


Summary

• Research on robotics and automation for biological applications is young (less than 10 years)

• U.S. is still leading the world in the numbers of laboratories and industries involved

• U.S. leads the world in identifying new applications• Theory and approaches are ad hoc, not systematic: “evolutionary not

revolutionary” (Meldrum)• There are many opportunities for collaboration between

biologists/doctors and engineers• Biology breakthrough needs revolutionary tools in engineering• The leading position of U.S. is being challenged.

robotics for biological and medical applications€¦ · robotics for biological and medical...

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