ロペズ ギヨーム
LOPEZ, Guillaume
Guillaume LOPEZ 所属 青山学院大学 理工学部 情報テクノロジー学科 職種 教授 |
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言語種別 | 英語 |
発行・発表の年月 | 2020/02 |
形態種別 | 学術雑誌 |
査読 | 査読あり |
標題 | The Influence of Person-specific Biometrics in Improving Generic Stress Predictive Models |
執筆形態 | 共同 |
掲載誌名 | Sensors and Materials |
出版社・発行元 | MYU K.K. |
巻・号・頁 | 32(2(2)),pp.703-722 |
著者・共著者 | Kizito Nkurikiyeyezu, Anna Yokokubo, Guillaume Lopez |
概要 | 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 |