This R&D Item aims to clarify the key components of Maemuki, or a constructive forward-oriented mindset, and to develop indicators and measurement approaches by integrating psychological, cognitive, bodily, and physiological information. We refined subjective measures through large-scale online surveys and advanced real-world assessments involving top athletes and cancer patients.
We also developed related measures, including those associated with flow experience, negative capability, and eudaimonic well-being. By combining laboratory and real-world data with AI-assisted analyses, we are building a scientific basis for assessing Maemuki-related states and developing predictive models.

Mechanisms of Embodied Maemuki

Using the Maemuki Scale developed to date, we conducted large-scale cross-sectional and longitudinal surveys and integrated cognitive, behavioral, and bodily data. We also developed cognitive tasks related to Maemuki, some of which showed associations with mood and memory.
Machine learning approaches were used to examine individual differences in positive illusion and to estimate cognitive and metacognitive characteristics. This approach also helped identify the factor structure of eudaimonic well-being and showed that these factors could be estimated from Maemuki scale items. In addition, we established a 24-item, 5-factor Negative Capability Scale to assess the capacity to remain engaged with uncertainty and ambiguity.

Real-World Sensing: Athletes and Cancer Patients

We conducted surveys and interviews with athletes and collected data in daily and competitive settings in collaboration with sports organizations. In snowboarding competitions, physiological and neural states measured immediately before performance were associated with competition rankings, suggesting their potential value for real-world assessment.
We also conducted surveys and interviews with more than 2,000 cancer patients. The results suggest that negative capability-related items may provide useful information for understanding psychological adaptation under adversity.

Flow Experience and the Generalization of Maemuki

We analyzed the relationship between flow experience and Maemuki and found that flow may be involved in the formation of Maemuki-related states. We also used EEG hyperscanning to examine team flow through inter-individual synchronization of neural and physiological signals.

Maemuki Sensing and Prediction

We developed predictive models for Maemuki-related states by integrating multiple types of bodily and physiological information. This work is being extended toward application-based tools for visualizing aspects of an individual’s mental state and supporting simple everyday assessment.

By integrating the Maemuki Scale, real-world data, AI-assisted analysis, and application-based assessment platforms, we will advance technologies that connect assessment, prediction, and support of Maemuki-related states.
We are currently developing a prototype AI platform, Body2Positive, which uses bodily information to estimate mental states. We will evaluate its accuracy and generalizability and aim to develop it as a support technology adaptable to individual conditions and everyday contexts.