CAREER Award: Helping More People Benefit From


image: Homa Alemzadeh, assistant professor of electrical and computer engineering and member of the Link Lab at the University of Virginia’s School of Engineering and Applied Science, will use her $550,000 CAREER award over five years to develop cyber systems -physics that work as a surgeon’s cognitive assistant, to detect and recover in real time events that could harm the patient.
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Credit: Tom Cogill

More than 60 million Americans live in rural communities and, according to the US Centers for Disease Control and Prevention, they are at greater risk of death from stroke, heart disease, cancer, emphysema and other chronic diseases. lower respiratory tract, compared to people who live in urban areas.

Breakthroughs in robotics offer hope for delivering the best treatments and timely care to underserved communities. In the United States, medical professionals are performing an increasing number of procedures assisted by surgical robots, and it is possible that surgeries performed remotely will become widespread in the future.

Homa Alemzadeh, an assistant professor of electrical and computer engineering at the University of Virginia School of Engineering and Applied Science, has won a prestigious National Science Foundation CAREER award for innovating in cyber-physical systems for robotic surgery . The CAREER program, one of NSF’s most prestigious awards for early career faculty, recognizes the recipient’s potential for leadership in research and education.

Alemzadeh’s research will enable better training of surgeons by providing feedback in the specific context of their work with patients, with the goal of expanding the availability and increasing the safety of robotic procedures.

“The NSF CAREER award is essential for developing and testing a fully integrated cyber-physical solution for security monitoring in virtual reality and dry lab training environments,” said Alemzadeh. “We hope to eventually see our system transition to real-world practice and provide safety assurance in real-world procedures, as a longer-term gain from this grant.”

Cyber-physical systems, control, and robotics are a combined research force of UVA’s Charles L. Brown Electrical and Computer Engineering Department and advance the mission of UVA Engineering’s Link Lab, to which Alemzadeh is affiliated. She also holds a courtesy position in the computer science department of UVA Engineering.

Surgical robots can make general, urological and gynecological procedures and certain cancer, brain and heart surgeries less invasive, reducing patient trauma and accelerating recovery. Alemzadeh will create safety monitoring tools programmed into robotic surgery units, designed to support a surgeon’s decision-making during a patient operation.

“Human experts are the final decision makers,” Alemzadeh said. “We seek to transfer their knowledge and expertise to the model and mechanisms we design, so that the system provides them with just-in-time, explainable feedback in response to every command.”

Medical cyber-physical systems involve hardware, software, and mechanical parts working with multiple humans in often busy operating or treatment rooms. Robotic surgery physically extends a surgeon’s hands and eyes. Cyber-physical systems for robotic surgery offer enhancements such as magnified 3D views and the ability to perform small movements more precisely and filter out tremors from surgeons’ hands.

Alemzadeh will use his CAREER award of $550,000 over five years to develop cyber-physical systems that function as a surgeon’s cognitive assistant, to detect and recover in real time from events that could harm the patient, regardless of the cause. – malicious cyberattacks, electrical and mechanical accidents malfunctions or software errors or unintentional human errors.

Alemzadeh will add hardware and software mechanisms to monitor what the surgeon and robot are doing in real time, and to anticipate and stop potentially dangerous actions before they become a risk. These mechanisms combine surgical workflow modeling, machine learning, signal processing, and decision processes to predict the most efficient recovery actions for the surgeon and robot to take when alerted to a potential damage.

A surgical cognitive assistant must be able to closely analyze and replicate the surgeon’s workflows, including behavioral patterns and movements. The first step is to model a given task, such as suturing, in a surgical procedure, using a set of standard granular motions, called motion primitives in robotics. The next step is to recognize motion primitives in more complex procedures and verify their execution to classify them as safe or potentially unsafe.

Members of Alemzadeh’s research group, Kay Hutchinson and Zongyu Li, Ph.D. electrical engineering students, have spent the past year defining and analyzing these surgical motion primitives and using them to develop models of recognition of execution gestures and detection of errors in robot-assisted surgery. Preliminary analyzes are reported in Analysis of Executional and Procedural Errors in Dry-lab Robotic Surgery Experiments, published February 2022 in the International Journal of Robotics and Computer Assisted Surgery and in Runtime Detection of Executional Errors in Robot-Assisted Surgery, recently presented at the IEEE International Conference on Robotics and Automation.

Members of Alemzadeh’s research group work closely with Dr. Noah Schenkman, John Kluge Professor of Urology at UVA School of Medicine, who performs robotic surgeries for UVA Health’s Department of Urology, and the Gynecologic oncologist Dr. Leigh Cantrell, associate professor in the Division of Residency Program Director of Gynecologic Oncology and Obstetrics and Gynecology.

UVA is one of the few universities where the top engineering and medical schools are within a one-mile radius of each other. This proximity accelerates the creation of knowledge at the intersection of engineering and medicine and explains why engineering for health is a leading research area for UVA Engineering.

A seed grant from the Center for Engineering in Medicine at the University of Virginia supported Alemzadeh’s early work to prove his concept on a simulator, allowing him to progress and submit preliminary results with his NSF grant proposal, even if the COVID-19 pandemic has temporarily interrupted the hospital. research based.

The principles and techniques are applicable to other types of robots and devices that augment human decision-making in complex and stressful situations such as medical triage and disaster response, Alemzadeh said.

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