The Center for Disease Control (CDC) estimates that 1.3 million older adults (age 65+) reside in nursing homes, with an additional 818,000 living in assisted living facilities in the USA. This number is expected to rise as the older adult population in the U.S. increases from 17% to 22% by 2040. The care of older adults in long-term care settings is often complicated by apathy, marked by a reluctance towards social interactions and loss of interest in daily activities. Apathy increases the burden on caregivers and is linked to accelerated cognitive decline, increased mortality, and diminished quality of life. Effective apathy interventions combine sensory and motorbased interactions with social engagement, but many require substantial resources that are unavailable in long-term care settings. Technological interventions, like virtual reality and socially assistive robotics, have shown promise in enhancing support for apathy interventions.
Our previous work developed a socially assistive robotic (SAR) and virtual reality (VR) (SAR-VR) system aimed at encouraging social engagement among older adults, utilizing the physical robot Nao and VR to create a safe and adaptable interaction environment. This system integrates physical, cognitive, and social components, promoting socialization through dyadic activities. The music activity, leveraging reminiscence therapy, uses Nao as a coach and socially interactive agent to provide feedback and instruction. This paper presents the design of a fuzzy inference system (FIS) for feedback management in a VR-based drumming and music activity aimed at apathy intervention. The system adapts FIS membership functions using real-world data from older adults in long-term care communities. In the intersection of humans and technology, the use of real-world data is paramount. Our results show that real-world data enables the creation of individualized FIS profiles, enhancing the naturalism and social component of interactions by fostering varied and personalized engagements between the robot and users. Enhancing the naturalism in human-robot communication and improving the socially interactive components of robot feedback is expected to create more engaging interactions, ultimately leading to more effective technological interventions for apathy.