Abstract:
Previous research in human-robot interaction has explored using robots to increase objective and hedonic aspects of well-being and quality of life, but there is no literature on how robots might be used to support eudaimonic aspects of well-being (such as meaning in life). A sense of meaning has been shown to positively affect health and longevity. We frame our study around the Japanese concept of ikigai, which is widely used with Japanese older adults to enhance their everyday lives, and is closely related to the concept of eudaimonic well-being (EWB) known in Western countries.
We started by conducting interviews and workshops with ikigai experts to ground our understanding of the term. Then, using a mixed-methods approach involving interviews, surveys, and live interactions with QT, we explored how older adults in the US and Japan experience ikigai and how QT might support further support it. These allowed us to build empirically test a model of cross-cultural ikigai.
Ongoing Work:
We are in the process of defining a number of activities and interventions that can support older adults’ ikigai, such as storytelling (timeslips) and reflection-based prompts.
Our technically-oriented ongoing work involves building deep learning models to determine ikigai and engagement during these activities, by using computer vision to determine when older adults are engaged with QT and discussing a topic related to their ikigai (iki-iki face), natural language processing (NLP) to use conversational content from interactions with QT, and audio waveforms to detect emotion through speech.