Streamlining Sensor Technology: Focusing on Data Fusion and Emotion Evaluation in the e-VITA Project

This paper explores the use of sensor-based multimodal data fusion and emotion detection technologies in e-VITA, a three-year EU–Japan collaborative project that developed an AI-powered virtual coaching system to support independent living for older adults. The system integrates these technologies t...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 25; no. 7; p. 2217
Main Authors: McTear, Michael, Jokinen, Kristiina, Roelen, Sonja Dana, Saif-Ur-Rehman, Muhammad, Hariz, Mossaab, Boudy, Jérôme, Lohr, Christophe, Szczepaniak, Florian, Wieching, Rainer, Ogawa, Toshimi
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 01.04.2025
MDPI
Subjects:
active and healthy ageing
Activities of daily living
Aged
Aging
Architecture
Artificial Intelligence
Chatbots
Decision making
emotion detection
Emotions
Emotions - physiology
Exercise
Exercise for the aged
Fuzzy logic
Humans
Japan
Life expectancy
Localization
Natural language
Neural networks
Older people
Pattern recognition
R&D
Research & development
Sensors
User experience
Japan
France
emotion detection
sensors
active and healthy ageing
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:This paper explores the use of sensor-based multimodal data fusion and emotion detection technologies in e-VITA, a three-year EU–Japan collaborative project that developed an AI-powered virtual coaching system to support independent living for older adults. The system integrates these technologies to enable individualized profiling and personalized recommendations across multiple domains, including nutrition, physical exercise, sleep, cognition, spirituality, and social health. Following a review of related work, we detail the implementation and evaluation of data fusion and emotion detection in e-VITA. The paper concludes with a summary of the key research findings and directions for future work.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s25072217