Next Article in Journal
OFDM with Index Modulation for Asynchronous mMTC Networks
Previous Article in Journal
Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(4), 1279; https://doi.org/10.3390/s18041279

A Wearable Gait Phase Detection System Based on Force Myography Techniques

MENRVA lab, Schools of Mechatronic Systems and Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada
*
Author to whom correspondence should be addressed.
Received: 20 March 2018 / Revised: 11 April 2018 / Accepted: 19 April 2018 / Published: 21 April 2018
(This article belongs to the Section Biosensors)
Full-Text   |   PDF [8953 KB, uploaded 3 May 2018]   |  

Abstract

(1) Background: Quantitative evaluation of gait parameters can provide useful information for constructing individuals’ gait profile, diagnosing gait abnormalities, and better planning of rehabilitation schemes to restore normal gait pattern. Objective determination of gait phases in a gait cycle is a key requirement in gait analysis applications; (2) Methods: In this study, the feasibility of using a force myography-based technique for a wearable gait phase detection system is explored. In this regard, a force myography band is developed and tested with nine participants walking on a treadmill. The collected force myography data are first examined sample-by-sample and classified into four phases using Linear Discriminant Analysis. The gait phase events are then detected from these classified samples using a set of supervisory rules; (3) Results: The results show that the force myography band can correctly detect more than 99.9% of gait phases with zero insertions and only four deletions over 12,965 gait phase segments. The average temporal error of gait phase detection is 55.2 ms, which translates into 2.1% error with respect to the corresponding labelled stride duration; (4) Conclusions: This proof-of-concept study demonstrates the feasibility of force myography techniques as viable solutions in developing wearable gait phase detection systems. View Full-Text
Keywords: FSR band; force sensors; gait phase; gait recognition FSR band; force sensors; gait phase; gait recognition
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

Share & Cite This Article

MDPI and ACS Style

Jiang, X.; Chu, K.H.; Khoshnam, M.; Menon, C. A Wearable Gait Phase Detection System Based on Force Myography Techniques. Sensors 2018, 18, 1279.

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