Next Article in Journal
Performance Evaluation of a Semi-Dual-Active-Bridge with PPWM Plus SPS Control
Next Article in Special Issue
Automatic Detection of Atrial Fibrillation and Other Arrhythmias in ECG Recordings Acquired by a Smartphone Device
Previous Article in Journal
Numerical-Sampling-Functionalized Real-Time Index Regulation for Direct k-Domain Calibration in Spectral Domain Optical Coherence Tomography
Previous Article in Special Issue
Closing the Wearable Gap: Mobile Systems for Kinematic Signal Monitoring of the Foot and Ankle
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessFeature PaperArticle
Electronics 2018, 7(9), 183;

Cost-Effective eHealth System Based on a Multi-Sensor System-on-Chip Platform and Data Fusion in Cloud for Sport Activity Monitoring

Departament d’Informàtica, Universitat de València, 46100 Burjassot, Spain
Department of Physiology, Universitat de València, 46010 València, Spain
Current address: Avda Universitat s/n, 46100, Burjassot, Spain.
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 10 August 2018 / Revised: 28 August 2018 / Accepted: 4 September 2018 / Published: 9 September 2018
(This article belongs to the Special Issue Data Processing and Wearable Systems for Effective Human Monitoring)
Full-Text   |   PDF [999 KB, uploaded 9 September 2018]   |  


eHealth systems provide medical support to users and contribute to the development of mobile and quality health care. They also provide results on the prevention and follow-up of diseases by monitoring health-status indicators and methodical data gathering in patients. Telematic management of health services by means of the Internet of Things provides immediate support and it is cheaper than conventional physical presence methods. Currently, wireless communications and sensor networks allow a person or group to be monitored remotely. The aim of this paper is to develop and assess a system for monitoring physiological parameters to be applied in different scenarios, such as health or sports. This system is based on a distributed architecture, where physiological data of a person are collected by several sensors; next, a Raspberry Pi joins the information and makes a standardization process; then, these data are sent to the Cloud to be processed. Our Cloud system stores the received data and makes a data fusion process in order to indicate the athlete’s fatigue status at every moment. This system has been tested in collaboration with a small group of voluntary tri-athletes. A network simulation has been performed to plan a monitoring network for a bigger group of athletes. Finally, we have found that this system is useful for medium-term monitoring of the sports activities. View Full-Text
Keywords: eHealth; sport; biomonitoring; sensor networks; Cloud; data fusion eHealth; sport; biomonitoring; sensor networks; Cloud; data fusion

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).

Share & Cite This Article

MDPI and ACS Style

Segura-Garcia, J.; Garcia-Pineda, M.; Tamarit-Tronch, M.; Cibrian, R.M.; Salvador-Palmer, R. Cost-Effective eHealth System Based on a Multi-Sensor System-on-Chip Platform and Data Fusion in Cloud for Sport Activity Monitoring. Electronics 2018, 7, 183.

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



[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top