Elderly Motion Analysis to Estimate Emotion: A Systematic Review

Article

Hassan, I., Nahid, N., Ahad, M. and Inoue, S. 2024. Elderly Motion Analysis to Estimate Emotion: A Systematic Review. International Journal of Activity and Behavior Computing. (2), pp. 1-23. https://doi.org/10.60401/ijabc.23
AuthorsHassan, I., Nahid, N., Ahad, M. and Inoue, S.
Abstract

This paper presents a systematic review focusing on motion analysisbased emotion estimation in the elderly. Addressing a critical concern, it highlights the challenge of effectively monitoring emotions in older adults and emphasizes the potential development of serious disorders resulting from emotional neglect. The study underscores the importance of emotional well-being in care facilities, where the willingness of elderly individuals to receive care is closely tied to their emotional state. Health practitioners often encounter difficulties when elderly individuals resist care due to emotional dissatisfaction, making monitoring changes in emotional states essential and necessitating comprehensive care records. Through an exhaustive examination of existing literature, the paper suggests that motion-based emotion recognition shows promise in addressing this challenge. Utilizing the PRISMA protocol, the study conducts a qualitative analysis of the impact of motion analysis on emotion estimation. It outlines the current methodologies employed in research and reveals a significant correlation between body motion cues and emotional states in the elderly. Furthermore, it positions motion-based emotion estimation as a viable solution for addressing emotional well-being in older adults and offers guidelines for researchers interested in this area. Based on our study we consider the first review of this kind on motion-based emotion estimation for the elderly, providing insights into potential advancements in addressing emotional well-being in this demographic.

Keywordselderly motion; emotion; AI
JournalInternational Journal of Activity and Behavior Computing
Journal citation(2), pp. 1-23
ISSN2759-2871
Year2024
Publisher Care XDX Center, Kyushu Institute of Technology
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Anyone
Digital Object Identifier (DOI)https://doi.org/10.60401/ijabc.23
Publication dates
Online13 Jun 2024
Publication process dates
Deposited15 Aug 2024
Copyright holder© 2024, The Author(s)
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