Next Article in Journal
Enhancing the Performance of the Data Embedment Process through Encoding Errors
Next Article in Special Issue
Recent Advances on Wearable Electronics and Embedded Computing Systems for Biomedical Applications
Previous Article in Journal
Component-Based Cartoon Face Generation
Previous Article in Special Issue
A Novel 12-Lead ECG T-Shirt with Active Electrodes
Article Menu

Export Article

Open AccessArticle
Electronics 2016, 5(4), 78; doi:10.3390/electronics5040078

Assessment of a Smart Sensing Shoe for Gait Phase Detection in Level Walking

1
Research Center “E. Piaggio”, University of Pisa, Largo Lucio Lazzarino 1, 56126 Pisa, Italy
2
Information Engineering Department, University of Pisa, via G. Caruso 16, 56122 Pisa, Italy
*
Author to whom correspondence should be addressed.
Academic Editors: Enzo Pasquale Scilingo and Mostafa Bassiouni
Received: 15 August 2016 / Revised: 31 October 2016 / Accepted: 4 November 2016 / Published: 16 November 2016
View Full-Text   |   Download PDF [4828 KB, uploaded 16 November 2016]   |  

Abstract

Gait analysis and more specifically ambulatory monitoring of temporal and spatial gait parameters may open relevant fields of applications in activity tracking, sports and also in the assessment and treatment of specific diseases. Wearable technology can boost this scenario by spreading the adoption of monitoring systems to a wide set of healthy users or patients. In this context, we assessed a recently developed commercial smart shoe—the FootMoov—for automatic gait phase detection in level walking. FootMoov has built-in force sensors and a triaxial accelerometer and is able to transmit the sensor data to the smartphone through a wireless connection. We developed a dedicated gait phase detection algorithm relying both on force and inertial information. We tested the smart shoe on ten healthy subjects in free level walking conditions and in a laboratory setting in comparison with an optical motion capture system. Results confirmed a reliable detection of the gait phases. The maximum error committed, on the order of 44.7 ms, is comparable with previous studies. Our results confirmed the possibility to exploit consumer wearable devices to extract relevant parameters to improve the subject health or to better manage his/her progressions. View Full-Text
Keywords: wearable technology; gait phase; gait cycle, accelerometers; force sensors; walking; smart shoe wearable technology; gait phase; gait cycle, accelerometers; force sensors; walking; smart shoe
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

Carbonaro, N.; Lorussi, F.; Tognetti, A. Assessment of a Smart Sensing Shoe for Gait Phase Detection in Level Walking. Electronics 2016, 5, 78.

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