Dr. Jaydev P. Desai is currently a Professor and BME Distinguished Faculty Fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech. He is also the Director of the Georgia Center for Medical Robotics (GCMR) and the Associate Director of the Institute for Robotics and Intelligent Machines (IRIM). He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. He was also a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient of several NIH R01 grants, NSF CAREER award, and was also the lead inventor on the “Outstanding Invention in Physical Science Category” at the University of Maryland, College Park, where he was formerly employed. He is also the recipient of the Ralph R. Teetor Educational Award. He has been an invited speaker at the National Academy of Sciences “Distinctive Voices” seminar series and was also invited to attend the National Academy of Engineering’s U.S. Frontiers of Engineering Symposium. He has over 160 publications, is the founding Editor-in-Chief of the Journal of Medical Robotics Research, and Editor-in-Chief of the Encyclopedia of Medical Robotics (currently in production). His research interests are primarily in the area of image-guided surgical robotics, rehabilitation robotics, cancer diagnosis at the micro-scale, and grasping. He is a Fellow of IEEE, ASME and AIMBE.
Areas of Expertise (4)
Image Guided Surgical Robotics
University of Pennsylvania: Ph.D., Mechanical Engineering 1998
Indiana Institute of Technology - Bombay: B. Tech, Mechanical Engineering 1993
Selected Media Appearances (3)
Horizons - Georgia Tech Research online
“It’s like having a surgeon’s fingers come out of the endoscope to manipulate the instruments,” said Jaydev Desai, director of the Georgia Center for Medical Robotics and a professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University.
Desai is collaborating with Dr. Joshua Chern, a neurosurgeon at Children’s, in research supported by a seed grant from the Imlay Innovation Endowment Fund at Children’s.
ASU’s Southwest Robotics Symposium previews the new technology guiding the next wave of human-robot interaction
ASU Now: Access, Excellence, Impact online
For example, the ability to 3D-print flexible materials has dramatically expanded the field of medical robotics, according to guest speaker Jaydev Desai, a professor from Georgia Institute of Technology.
Desai’s micro-scale, robotically actuated guidewires present a new option for procedures like cardiovascular surgery, replacing rigid, difficult-to-insert instruments with soft, jointed devices.
“Look at your finger,” Desai instructed the attendees. “Imagine a guidewire that could afford independent flexibility at any of the three joints, like your finger," he said. “This significantly enhances a surgeon’s ability to navigate a complicated pathway of arteries without causing damage along the way."
IEEE Names Extraordinary Indian American Engineers Newly Elevated Fellows for 2018
India West online
Jaydev Desai of the Georgia Institute of Technology in Atlanta was selected for contributions to medical and swarm robotics. Saibal Mukhopadhyay, also of Georgia Tech, was selected for contributions to energy-efficient and robust computing systems design.
Selected Articles (6)
Robotic artificial muscles are a subset of artificial muscles that are capable of producing biologically inspired motions useful for robot systems, i.e., large power-to-weight ratios, inherent compliance, and large range of motions. These actuators, ranging from shape memory alloys to dielectric elastomers, are increasingly popular for biomimetic robots as they may operate without using complex linkage designs or other cumbersome mechanisms. Recent achievements in fabrication, modeling, and control methods have significantly contributed to their potential utilization in a wide range of applications. However, no survey paper has gone into depth regarding considerations pertaining to their selection, design, and usage in generating biomimetic motions.
This paper presents the development of a fiber Bragg grating (FBG) bending sensor for shape memory alloy (SMA) bending modules. Due to the small form factor, low cost, and large-deflection capability, SMA bending modules can be used to construct disposable surgical robots for a variety of minimally invasive procedures. To realize a closed-loop control of SMA bending modules, an intrinsic bending sensor is imperative. Due to the lack of bending sensors for SMA bending modules, we have developed an FBG bending sensor by integrating FBG fibers with a superelastic substrate using flexible adhesive. Since the substrate is ultra-thin and adhesive is flexible, the sensor has low stiffness and can measure large curvatures. Additionally, due to the orthogonal arrangement of the sensor/actuator assembly, the influence of temperature variation caused by SMA actuation can be compensated.
Surgical robots have been extensively researched for a wide range of surgical procedures due to the advantages of improved precision, sensing capabilities, motion scaling, and tremor reduction, to name a few. Though the underlying disease condition or pathology may be the same across patients, the intervention approach to treat the condition can vary significantly across patients. This is especially true for endovascular interventions, where each case brings forth its own challenges. Hence, it is critical to develop patient-specific surgical robotic systems to maximize the benefits of robot-assisted surgery. Manufacturing patient-specific robots can be challenging for complex procedures and, furthermore, the time required to build them can be a challenge.
Flexible sensors using functional materials have been extensively studied due to their significant potential in biomedical applications such as wearable electronics. Multi-walled carbon nanotubes (MWCNTs) that have excellent electrical conductivity enables polydimethylsiloxane (PDMS), a biocompatible silicone, to become conductive and piezoresistive as a nano-filler material in the polymer. Dispersion methods of MWCNT in PDMS and characterization of MWCNT/PDMS elastomers are analyzed to establish an optimal fabrication process. The fabricated MWCNT/PDMS-based flexible sensors have been implemented for two medical applications: 1) tactile sensing for a robotic hand for rehabilitation tasks and 2) strain sensing within a needle for in situ tissue characterization. Since the developed piezoresistive type of sensors are highly flexible, responsive, easy to scale, cost-effective, simply packaged, and
Spinal cord injury (SCI) to the C-5 area causes loss of fine motor control in the hand and fingers. Stroke often causes hemiparesis, which impairs arm and hand function. Both afflictions render the individual unable to complete activities of daily living (ADL). In this work, an exotendon glove system is designed for repetitive task practice (RTP) to improve the efficacy of hand and finger function rehabilitation in spinal cord injury patients. Common ADL tasks are evaluated through correlation analysis to aid in the design of the exotendon glove. A novel slack-enabling mechanism is introduced and a smartphone app voice control interface is developed to increase the efficiency and effectiveness of the exotendon glove. The range-of-motion (ROM) of the exotendon glove in individual finger movement and ADL tasks is experimentally identified, and the performance of the exotendon glove in ADL tasks is experimentally
We present a modular sensing system to measure the deflection of a minimally invasive neurosurgical intracranial robot (MINIR): MINIR-II. The MINIR-II robot is a tendon-driven continuum robot comprised of multiple spring backbone segments, which has been developed in our prior work. Due to the flexibility of the spring backbone and unique tendon routing configuration, each segment of MINIR-II can bend up to a large curvature (≥100 m-1) in multiple directions. However, the shape measurement of the robot based on tendon displacement is not precise due to friction and unknown external load/disturbance. In this regard, we propose a bending sensor module comprised of a fiber Bragg grating (FBG) fiber, a Polydimethylsiloxane (PDMS) cylinder, and a superelastic spring. The grating segment of the FBG fiber is enclosed inside a PDMS cylinder (1 mm in diameter), and the PDMS cylinder is bonded with the