S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
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)

Copyright(C) MYU K.K.

Approximate Model for Stress Assessment Using Electroencephalogram Signal

Ying Lin, Hai-Feng Chen, Hui-Hong Chen, Zhen-Lun Yang, Ting-Cheng Chang, and Zeng-Rong Zhan

(Received September 6, 2021; Accepted December 2, 2021)

Keywords: EEG, ECG, stress, wearable, approximate model

Mental stress is a problem that people may often face. Although there are some psychobiological stress measurement methods based on electroencephalogram (EEG) signals, these methods use expensive medical equipment to gather multichannel signals and cannot measure stress in real-time in daily life. Many novel wearable devices now have a sensor for physiological signal detection, which helps people manage health conditions. Several studies have recently investigated the application of wearable devices to stress detection. In this paper, an approximate model based on an EEG signal is designed for measuring stress. To establish the connection between the EEG and electrocardiogram signals, we use wearable devices to simultaneously collect the two types of data from volunteers. The exponentially weighted moving average is used to smooth out the EEG power spectrum features (α, β, etc.). An EEG-based feature vector is constructed to predict stress scores, with polynomial regression used to build the model. The experimental results show that the proposed method achieves a symmetric mean absolute percentage error of 17.44 and a root mean square error of 11.26.

Corresponding author: Ting-Cheng Chang




Forthcoming Regular Issues


Forthcoming Special Issues

Special Issue on Advanced Technologies for Remote Sensing and Geospatial Analysis Part 1
Guest editor, Dong Ha Lee (Kangwon National University) and Myeong Hun Jeong (Chosun University)
Call for paper


Special Issue on Advanced Micro and Nanomaterials for Various Sensor Applications (Selected Papers from ICASI 2020)
Guest editor, Sheng-Joue Young (National Formosa University), Shoou-Jinn Chang (National Cheng Kung University), Liang-Wen Ji (National Formosa University), and Yu-Jen Hsiao (Southern Taiwan University of Science and Technology)
Conference website
Call for paper


Special Issue on International Conference on BioSensors, BioElectronics, BioMedical Devices, BioMEMS/NEMS and Applications 2019 (Bio4Apps 2019) (2)
Guest editor, Hirofumi Nogami and Masaya Miyazaki (Kyushu University)
Conference website


8th Special Issue on the Workshop of Next-generation Front-edge Optical Science Research
Guest editor, Yutaka Fujimoto (Tohoku University) and Takayuki Yanagida (Nara Institute of Science and Technology)


Special Issue on Advanced Materials and Sensing Technologies on IoT Applications: Part 3-1
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)


Special Issue on Recent Advances in Soft Computing and Sensors for Industrial Applications
Guest editor, Chih Hsien Hsia (National Ilan University)
Call for paper


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