LOPEZ, Guillaume
Department Aoyama Gakuin University Department of Integrated Information Technology, College of Science and Engineering Position Professor |
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Language | English |
Publication Date | 2020/02 |
Type | Academic Journal |
Peer Review | Peer reviewed |
Title | The Influence of Person-specific Biometrics in Improving Generic Stress Predictive Models |
Contribution Type | Collaboration |
Journal | Sensors and Materials |
Publisher | MYU K.K. |
Volume, Issue, Page | 32(2(2)),pp.703-722 |
Author and coauthor | Kizito Nkurikiyeyezu, Anna Yokokubo, Guillaume Lopez |
Details | Because stress is subjective and is expressed differently from one person to another, generic stress prediction models (i.e., models that predict the stress of any person) perform crudely. Only person-specific models (i.e., ones that predict the stress of a preordained person) yield reliable predictions, but they are not adaptable and are costly to deploy in realworld environments. For illustration, in an office environment, a stress monitoring system that uses person-specific models would require the collection of new data and the training of a new model for every employee. Moreover, once deployed, the models would deteriorate and need expensive periodic upgrades because stress is dynamic and depends on unforeseeable factors. We propose a simple, yet practical and cost-effective calibration technique that derives an accurate and personalized stress prediction model from physiological samples collected from a large population. |
DOI | 10.18494/SAM.2020.2650 |
ISSN | 2435-0869 |