Can Robot Patients Lead to Better Doctors?
Research seeks to make better human patient simulators, a training tool that enables clinicians to practice their skills before treating real patients.
Yet learning to read those clues could yield lifesaving results. Preventable medical errors in hospitals are the third-leading cause of death in the United States.
“What’s really striking about this is that these deaths are completely preventable,” Riek said.
One factor contributing to those accidents is clinicians missing clues and going down incorrect diagnostic paths, using incorrect treatments or wasting time. Reading facial expressions, Riek said, can help doctors improve those diagnoses. It is important that their training reflects this.
In addition to modeling and synthesizing patient facial expressions, Riek and her team are building a new, fully-expressive robot head. By employing 3-D printing, they are working to produce a robot that is low-cost and will be one day available to both researchers and hobbyists in addition to clinicians.
The team has engineered the robot to have interchangeable skins, so that the robot’s age, race and gender can be easily changed. This will enable researchers to explore social factors or “cultural competency” in new ways.
“Clinicians can create different patient histories and backgrounds and can look at subtle differences in how healthcare workers treat different kinds of patients,” Riek said.
Riek’s work has the potential to help address the patient safety problem, enabling clinicians to take part in simulations otherwise impossible with existing technology.
This article was republished in its entirety with the permission of the National Science Foundation (NSF). The NSF is an independent federal agency created by Congress in 1950 “to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense…”