Format

Send to

Choose Destination
Sensors (Basel). 2016 Dec 3;16(12). pii: E2053.

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

Author information

1
Department of Information and Telecommunications Engineering, Ming Chuan University, Gui-Shan, Taoyuan 333, Taiwan. sychiang@mail.mcu.edu.tw.
2
Department of Communications Engineering, Yuan Ze University, Chung-Li, Taoyuan 320, Taiwan. yckan@saturn.yzu.edu.tw.
3
Department of Physical Therapy, China Medical University, 91 Hsueh-Shi Road, Taichung 40402, Taiwan. u103009405@cmu.edu.tw.
4
Department of Information and Telecommunications Engineering, Ming Chuan University, Gui-Shan, Taoyuan 333, Taiwan. conanto1986@hotmail.com.
5
Department of Health Risk Management, China Medical University, 91 Hsueh-Shi Road, Taichung 40402, Taiwan. snowlin@mail.cmu.edu.tw.

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.

KEYWORDS:

WSN; accelerometer; activity recognition; gyroscope; neuro fuzzy; ubiquitous health care

PMID:
27918482
PMCID:
PMC5191034
DOI:
10.3390/s16122053
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Multidisciplinary Digital Publishing Institute (MDPI) Icon for PubMed Central
Loading ...
Support Center