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Robotically precise diagnostics and therapeutics for degenerative disc disorder
Lower back pain caused by degenerative disc disorder affects approximately 40% of the population over 40 and though many of us may never experience adverse effects from the disorder, it is the cause of chronic back pain for numerous Americans. Recent imaging diagnostics and cellular based direct-injection therapeutics for degenerative disc and spinal cord injuries have shown great promise for chronic back pain sufferers, however the targeted area for delivery is very small and narrow, requiring extreme precision by the clinical practitioner to avoid the bony vertebrae and other sensitive tissues.
The normative anatomy of the spinal area is quite complex. Between each vertebra is a 'disc' of fibrous cartilage surrounding a sac of gel-like fluid that act as the spine's shock absorbers, as well as giving the spine flexibility. Primary nerve branches to the various location of the body travel through this area from the central spinal canal. The complexity is increased if the patient has pre-existing conditions such as bone abnormalities due to scoliosis or osteoarthritis, spinal stenosis (a narrowing of the spinal canal causing compression) or have surgical implants, such as plates, rods and screws. Depending on the type of therapy, number of injections required, and the injection positioning complexity, spinal injection therapy treatment time frames can range from ~15 minutes to two hours, excluding post-procedure recovery time.
To increase injection site positioning preciseness, and thus the effectiveness, of these new treatments the Biorobotics and Human Modeling Lab, under the direction of George W. Woodruff School of Mechanical Engineering Professor Jun Ueda, have developed a patient mounted injection needle robot for use in magnetic resonance elastography (MRE), a technology that combines MRI imaging and low-frequency vibrations to create a map (elastogram) that images the stiffness of soft tissues. Working in conjunction with the Stevens Institute of Technology and the Mount Sinai Hospital, the team developed non-ferromagnetic lead zirconate titanate (PZT) actuators that allow for usage in the magnetic field area produced by MR imaging. The team used the prototype in a demonstration MRE scan for improved diagnosis of degenerative disc diseases. Multi-source shear wave propagation for examination of the pathological state of the patient tissue is achieved by tunable resonant frequency of the individual actuators. This allows for a minimally invasive procedure with a significant increase in precision needle positioning than that available via a human clinician.
This Research was Sponsored by the following: NSF 1662029, CDMRP FY 2019 Discovery Award, IRIM seed grant FY 2018 & FY 2019, NSF 1545287 (student fellowship | Meinhold, Martinez)
Robot Swarms Guided by Human Artists Could Paint Colourful Pictures
Small swarms of robots could help artists paint pictures. María Santos at the Georgia Institute of Technology and her colleagues designed a system that would allow an artist using a computer to select regions of a canvas to be painted in certain colours. These are then created in real-time by 12 robots that cross the canvas leaving trails of colour behind them.
“We envisioned the multi-robot system as an extension of an artist’s creative palette,” says Santos. “Because the human only controls the collective behaviour of the team, the multi-robot team can be [thought] of as an active brush for the human artist to paint with.”
Currently, the robots don’t carry real paint. Instead, the researchers tested their ability to work together using projectors that simulated coloured paint trails behind the robots on the canvas. Each of the robots can produce three primary colours – magenta, cyan and yellow – which can also be combined to produce additional hues. Read more here.
Researcher Update: María Santos
María Santos is now a Postdoctoral Research Associate in the Department of Mechanical and Aerospace Engineering at Princeton University, where she works with Dr. Naomi Leonard. She completed her PhD in Electrical and Computer Engineering at the Georgia Institute of Technology, advised by Dr. Magnus Egerstedt. Her research focuses on the distributed coordination of multi-robot systems, with a particular focus on modeling heterogeneous capabilities within large swarms of robots.