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

Toshimi Ogawa, Rainer Wieching, Michael McTear, Kristiina Jokinen, Sonja Dana Roelen, Muhammad Saif-Ur-Rehman, Mossaab Hariz, Jérôme Boudy, Christophe Lohr, Florian Szczepaniak

Journal: Sensors (Basel, Switzerland) 2025;25(7):

PMID: 40218729

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Abstract

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.

Address: School of Computing, Ulster University, Belfast BT155 1AP, UK.; Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIRC/AIST), Tokyo 135-0064, Japan.; Institut für Experimentelle Psychophysiologie GmbH (IXP), 40215 Düsseldorf, Germany.; Institut Mines-Télécom (IMT), 91120 Palaiseau, France.; Business Information Systems and New Media, Universität Siegen (USI), Faculty III, 57068 Siegen, Germany.; Institute for Development, Aging and Cancer, Tohoku University, Sendai 980-8577, Japan.

DOI: 10.3390/s25072217

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MeSH Terms: Humans, Emotions, Artificial Intelligence, Aged, Japan