Next Article in Journal
A Fault Tolerance Mechanism for On-Road Sensor Networks
Next Article in Special Issue
An Approach to Biometric Verification Based on Human Body Communication in Wearable Devices
Previous Article in Journal
Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments
Previous Article in Special Issue
Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)—A Survey
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(12), 2053; doi:10.3390/s16122053

Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement

1
Department of Information and Telecommunications Engineering, Ming Chuan University, Gui-Shan, Taoyuan 333, Taiwan
2
Department of Communications Engineering, Yuan Ze University, Chung-Li, Taoyuan 320, Taiwan
3
Department of Physical Therapy, China Medical University, 91 Hsueh-Shi Road, Taichung 40402, Taiwan
4
Department of Health Risk Management, China Medical University, 91 Hsueh-Shi Road, Taichung 40402, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Giancarlo Fortino, Hassan Ghasemzadeh, Wenfeng Li, Yin Zhang and Luca Benini
Received: 4 October 2016 / Revised: 22 November 2016 / Accepted: 23 November 2016 / Published: 3 December 2016
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
View Full-Text   |   Download PDF [4253 KB, uploaded 3 December 2016]   |  

Abstract

Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC. View Full-Text
Keywords: WSN; accelerometer; gyroscope; activity recognition; neuro fuzzy; ubiquitous health care WSN; accelerometer; gyroscope; activity recognition; neuro fuzzy; ubiquitous health care
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chiang, S.-Y.; Kan, Y.-C.; Chen, Y.-S.; Tu, Y.-C.; Lin, H.-C. Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement. Sensors 2016, 16, 2053.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top