Embodied virtual agents serving as patient simulators are widely used in medical training scenarios, ranging from physical patients to virtual patients presented via virtual and augmented reality technologies. Physical-virtual patients are a hybrid solution that combines the benefits of dynamic visuals integrated into a human-shaped physical form that can also present other cues, such as pulse, breathing sounds, and temperature. Sometimes in simulation the visuals and shape do not match. We carried out a human-participant study employing graduate nursing students in pediatric patient simulations comprising conditions associated with matching/non-matching of the visuals and shape.

Conventional Intelligent Virtual Agents (IVAs) focus primarily on the visual and auditory channels for both the agent and the interacting human: the agent displays a visual appearance and speech as output, while processing the human's verbal and non-verbal behavior as input. However, some interactions, particularly those between a patient and healthcare provider, inherently include tactile components. We introduce an Intelligent Physical-Virtual Agent (IPVA) head that occupies an appropriate physical volume; can be touched; and via human-in-the-loop control can change appearance, listen, speak, and react physiologically in response to human behavior. Compared to a traditional IVA, it provides a physical affordance, allowing for more realistic and compelling human-agent interactions. In a user study focusing on neurological assessment of a simulated patient showing stroke symptoms, we compared the IPVA head with a high-fidelity touch-aware mannequin that has a static appearance. Various measures of the human subjects indicated greater attention, affinity for, and presence with the IPVA patient, all factors that can improve healthcare training.

We demonstrate a generalizable method for unified multitouch detection and response on a human head-shaped surface with a rear-projection animated 3D face. The method helps achieve hands-on touch-sensitive training with dynamic physical-virtual patient behavior. The method, which is generalizable to other non-parametric rear-projection surfaces, requires one or more infrared (IR) cameras, one or more projectors, IR light sources, and a rear-projection surface. IR light reflected off of human fingers is captured by cameras with matched IR pass filters, allowing for the localization of multiple finger touch events. These events are tightly coupled with the rendering system to produce auditory and visual responses on the animated face displayed using the projector(s), resulting in a responsive, interactive experience. We illustrate the applicability of our physical prototype in a medical training scenario.