Young Researcher Paper Award 2023
🥇Winners

Notice of retraction
Vol. 34, No. 8(3), S&M3042

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 4(1) (2020)
Copyright(C) MYU K.K.
pp. 1209-1221
S&M2171 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2527
Published: April 10, 2020

Human Fall Detection Algorithm Design Based on Sensor Fusion and Multi-threshold Comprehensive Judgment [PDF]

Junsuo Qu, Chen Wu, Qian Li, Ting Wang, and Abdel Hamid Soliman

(Received July 15, 2019; Accepted October 18, 2019)

Keywords: fall detection, eigenvalues, support vector, SVM fall model

The use of a single method of acceleration threshold discrimination cannot fully characterize the change in human fall behavior, which can easily result in misjudgment. In this paper, we propose a human fall detection algorithm that combines human posture, support vector machine (SVM), and quadratic threshold decision. Firstly, a large number of human posture data are collected through a six-axis inertial measurement module (MPU6050). A fall detection model is established through filtering preprocessing, eigenvalue extraction, classification, and SVM training. Secondly, a first-level threshold determination is performed through a wearable wristband device. When a suspected fall occurs, six eigenvalues will be captured and uploaded to a cloud platform to trigger second-level SVM fall judgments. By matching the eigenvalues with the fall detection model, it can be determined accurately whether a fall has taken place. The experimental results show that the fall detection has a recognition rate of 92.2%, a false rate of 3.593%, and missing rate of 2.187%, which can better distinguish other nonfall actions.

Corresponding author: Junsuo Qu


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

Cite this article
Junsuo Qu, Chen Wu, Qian Li, Ting Wang, and Abdel Hamid Soliman, Human Fall Detection Algorithm Design Based on Sensor Fusion and Multi-threshold Comprehensive Judgment, Sens. Mater., Vol. 32, No. 4, 2020, p. 1209-1221.



Forthcoming Regular Issues


Forthcoming Special Issues

Applications of Novel Sensors and Related Technologies for Internet of Things
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 Data Sensing and Processing Technologies for Smart Community and Smart Life
Guest editor, Tatsuya Yamazaki (Niigata University)
Call for paper


Special Issue on Advanced Sensing Technologies and Their Applications in Human/Animal Activity Recognition and Behavior Understanding
Guest editor, Kaori Fujinami (Tokyo University of Agriculture and Technology)
Call for paper


Special Issue on International Conference on Biosensors, Bioelectronics, Biomedical Devices, BioMEMS/NEMS and Applications 2023 (Bio4Apps 2023)
Guest editor, Dzung Viet Dao (Griffith University) and Cong Thanh Nguyen (Griffith University)
Conference website
Call for paper


Special Issue on Piezoelectric Thin Films and Piezoelectric MEMS
Guest editor, Isaku Kanno (Kobe University)
Call for paper


Special Issue on Advanced Micro/Nanomaterials for Various Sensor Applications (Selected Papers from ICASI 2024)
Guest editor, Sheng-Joue Young (National United University)
Conference website
Call for paper


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