Abstract
As the aging population around the world, figuring out the reason for changes in the health status of elderly adults at home is pressing. In our research group, to comprehend the scientific self-care of elderly adults at home, a core concept called “mind externalization” that retrieves the elders’ thoughts as much as possible using spoken dialogue agent technology has developed swiftly. The purpose of this paper is to consider an approach to elucidating reasons for health changes in the elderly at home. Our key idea is to merge the results of health status, dialogue logs, and emotional values (recognized from images and audio during the spoken dialogue) into a time series. More specifically, we describe an approach for extracting the features of changes in health data (i.e., heart rate, stress, sleep quality, step, and activity level from the wearable device). It intends to add health data retrieved from a wearable device and unite heterogeneous data (i.e., health data and dialogue data). Based on the integration between health data and dialogue data (i.e., text logs, audio, and images), we discuss an approach to estimating the reasoning context before and after the period. In this way, assisting elderly adults at home by grasping their daily living in detail can be appreciated. Meanwhile, executing personalized self-management is promising.
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Notes
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https://www.garmin.co.jp/minisite/health/guide/ (in Japanese).
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Acknowledgements
This research was partially supported by JSPS KAKENHI Grant Numbers JP19H01138, JP18H03242, JP18H03342, JP19H04154, JP19K02973, JP20K11059, JP20H04014, JP20H05706 and Tateishi Science and Technology Foundation (C) (No. 2207004).
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Chen, S., Ozono, H., Nakamura, M. (2022). Integration Analysis of Heterogeneous Data on Mind Externalization of Elderly People at Home. In: Gao, Q., Zhou, J. (eds) Human Aspects of IT for the Aged Population. Technology in Everyday Living. HCII 2022. Lecture Notes in Computer Science, vol 13331. Springer, Cham. https://doi.org/10.1007/978-3-031-05654-3_13
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