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.

The field of intelligent virtual agents (IVAs) has evolved immensely over the past 15 years, introducing new application opportunities in areas such as training, health care, and virtual assistants. In this survey paper, we provide a systematic review of the most influential user studies published in the IVA conference from 2001 to 2015 focusing on IVA development, human perception, and interactions. A total of 247 papers with 276 user studies have been classified and reviewed based on their contributions and impact. We identify the different areas of research and provide a summary of the papers with the highest impact. With the trends of past user studies and the current state of technology, we provide insights into future trends and research challenges.

The field of augmented reality (AR) has introduced many novel input and output approaches for human-computer interaction. As touching physical objects with the fingers or hands is both natural and intuitive, touch-based graphical interfaces are ubiquitous, but many such interfaces are limited to flat screens or simple objects. We propose an optical method for multi-touch detection and response on non-parametric surfaces with dynamic rear-projected imagery, which we demonstrate on two head-shaped surfaces. We are interested in exploring the advantages of this approach over two-dimensional touch input displays, particularly in healthcare training scenarios.

While research in the field of augmented reality (AR) has produced many innovative human-computer interaction techniques, some may produce physical and visual perceptions with unforeseen negative impacts on user performance. In a controlled human-subject study we investigated the effects of mismatched physical and visual perception on cognitive load and performance in an AR touching task by varying the physical fidelity (matching vs. non-matching physical shape) and visual mechanism (projector-based vs. HMD-based AR) of the representation. Participants touched visual targets on four corresponding physical-visual representations of a human head. We evaluated their performance in terms of touch accuracy, response time, and a cognitive load task requiring target size estimations during a concurrent (secondary) counting task. After each condition, participants completed questionnaires concerning mental, physical, and temporal demands; stress; frustration; and usability. Results indicated higher performance, lower cognitive load, and increased usability when participants touched a matching physical head-shaped surface and when visuals were provided by a projector from underneath.

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.