Young Researcher Paper Award 2021
🥇Winners

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 32, Number 2(2) (2020)
Copyright(C) MYU K.K.
pp. 703-722
S&M2131 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2650
Published: February 20, 2020

Effect of Person-specific Biometrics in Improving Generic Stress Predictive Models [PDF]

Kizito Nkurikiyeyezu, Anna Yokokubo, and Guillaume Lopez

(Received October 4, 2019; Accepted November 26, 2019)

Keywords: continuous stress monitoring, physiological computing, heart rate variability, electrodermal activity, smart buildings

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. We validate our approach on two stress datasets. The results show that our technique performs much better than a generic model. For instance, a generic model achieved only 42.5 ± 19.9% accuracy. However, with only 100 calibration samples, we raised its accuracy to 95.2 ± 0.5%. We also propose a blueprint for a stress monitoring system based on our strategy, and we debate its merits and limitations. Finally, we made our source code and the relevant datasets public to allow other researchers to replicate our findings.

Corresponding author: Kizito Nkurikiyeyezu


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Kizito Nkurikiyeyezu, Anna Yokokubo, and Guillaume Lopez, Effect of Person-specific Biometrics in Improving Generic Stress Predictive Models, Sens. Mater., Vol. 32, No. 2, 2020, p. 703-722.



Forthcoming Regular Issues


Forthcoming Special Issues

Special Issue on Advanced Materials and Sensing Technologies on IoT Applications: Part 4-3
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)


Special Issue on Advanced Technologies for Remote Sensing and Geospatial Analysis: Part 2
Guest editor, Dong Ha Lee (Kangwon National University) and Myeong Hun Jeong (Chosun University)
Call for paper


Special Issue on IoT Wireless Networked Sensing for Life and Safety
Guest editor, Toshihiro Itoh (The University of Tokyo) and Jian Lu (National Institute of Advanced Industrial Science and Technology)
Call for paper


Special Issue on Biosensors and Biofuel Cells for Smart Community and Smart Life
Guest editor, Seiya Tsujimura (University of Tsukuba), Isao Shitanda (Tokyo University of Science), and Hiroaki Sakamoto (University of Fukui)
Call for paper


Special Issue on Novel Sensors and Related Technologies on IoT Applications: Part 1
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
Call for paper


Special Issue on Advanced Ubiquitous Computing Systems for Society 5.0
Guest editor, Manato Fujimoto (Osaka City University)
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.