FOCUS:
Home Robots · Well-Being
ROLE:
Innovation Strategist · Product Manager · Prototype Researcher
DELIVERABLES:
Design & Feature Prioritization Guidance
CONTEXT:
United States and Japan · Mixed Methods· Multi-Year
Supporting Meaning in Later Life Through Robotics
Exploring how home robots can support ikigai (eudaimonic well-being, meaning) across cultures using predictive modeling, behavioral design, and human insight
Impact at a Glance
How might we support ikigai (a Japanese term roughly translating to meaning and purpose) through robotic technologies for older adults in culturally sensitive and personally resonant ways? This meant defining and measuring ikigai across U.S. and Japanese contexts, aligning robot behaviors to the lived experiences of older adults, and determining which features to build and how to evaluate them early.
Indiana University · Tsukuba University · Toyota Research Institute
Multi-institutional collaboration across academia and industry.
Innovation Strategist · Product Manager · Prototype Research Lead
I drove the end-to-end strategy and execution for this cross-cultural study and product exploration. I conducted an extensive literature review contrasting U.S. and Japanese views of meaning, happiness, and aging. I created, scripted, narrated, and edited the concept video used to evaluate early-stage responses to the robot. I designed and implemented conversational and nonverbal behaviors on the robot for initial live testing using simulated interaction (Wizard-of-Oz), to evaluate value and feasibility prior to full development. I used conversational analysis to highlight improvements needed to the robot's prompts, responses, and timing. I suggested robot features and led feature prioritization to align interventions with ikigai’s core dimensions. I built and tested predictive models (e.g., decision trees, SVMs) to identify drivers of meaning and engagement. I conducted and analyzed interviews, developed and analyzed surveys, and helped launch the Japan pilot, training researchers and ensuring cultural fit.
We conducted a mixed-methods, cross-cultural study to examine how socially assistive robots could support older adults’ sense of meaning and purpose (ikigai). This research combined two online surveys (ikigai, robot perception), in-person robot interaction sessions, and semi-structured qualitative interviews with older adults in both the U.S. and Japan. An extensive literature review informed the initial study design, focusing on cultural differences in how ikigai, meaning, and happiness are conceptualized. A concept video served as a key research stimulus to introduce the robot and its intended role.
Initial robot sessions used simulated interaction (Wizard-of-Oz) to test early-stage conversational and nonverbal behaviors prior to development. In parallel, a memory-sharing pilot study explored whether older adults would engage in storytelling with the robot when prompted by generic photographic images (e.g., a beach, a child playing with a ball). This work helped shape the design of future interaction features aimed at eliciting personal reflection.
Behavioral data from the interaction sessions were video recorded and manually coded to identify markers of user engagement. Coders logged behaviors such as gaze, smiles, laughter, and conversational turn-taking to assess the quality of interaction over time. Additionally, a conversation analysis was conducted to explore how participants responded to different types of robot prompts and how these exchanges evolved.
Early predictive models, including decision trees and support vector machines, were developed to estimate engagement levels and feature preference based on participant responses. Insights from the study informed both feature development and the framing of interventions in later design stages.
Whiteboarding Concepts and Flow in Miro
Initial Woz Testing
Engagement and Ikigai Models
Line-by-Line Conversational Analysis with Iterative Script Updates
Module & Model Development
Post-AI Model Implementation
Seven actionable design strategies were developed to help robots support meaning-making in older adults, based on cross-cultural insights:
Strengthen family bonds
Encourage connection with loved ones through reminders, shared stories, or prompts for family interaction.Promote small acts of contribution
Suggest meaningful ways to help others, from daily gestures to informal support roles.Offer volunteer opportunities
Recommend age-appropriate, emotionally rewarding opportunities to give back.Reinforce existing sources of meaning
Prompt engagement in hobbies, roles, or routines that already bring purpose.Introduce new meaningful experiences
Suggest novel activities aligned with the user’s values and interests.Encourage daily reflection
Use conversation or journaling prompts to help users reflect on their day and emotions.Elicit positive memories
Invite users to share meaningful stories and life moments with the robot.
Ikigai ≠ happiness
Emotional well-being and purpose often came from distinct sources; robots must address both.
Culture drives need
Japanese participants preferred a robot that offer advanced conversational ability, while U.S. users wanted a functionality first model.
Reflection builds meaning
Daily reflection prompts from the robot improved user perceptions of purpose.
Behavioral design matters
Empathetic gestures, light humor, and proactive suggestions increased positive affect.
Living situation shapes desire
Participants living alone responded differently to social features and companionship.
Ikigai should inform design
Seven categories of ikigai were used to craft more targeted robotic interventions.
Culture shapes product logic
U.S. and Japanese participants differed not only in preferences but in underlying motivations—highlighting the need for culturally attuned feature design and behavioral framing.
Behavioral hypotheses add strategic clarity
Early framing around emotional vs. motivational support helped align the team and prioritize features grounded in real user needs.
Universal features aren’t universal
Seemingly global solutions (like journaling or goal setting) were interpreted differently across cultures, reinforcing the need for localization even in emotional well-being tools.
Strategy needs field grounding
Being on-site in Japan and the U.S. revealed insights that remote research alone would’ve missed—especially around tone, pacing, and interaction norms.
