Next Article in Journal
A Power-Optimized Cooperative MAC Protocol for Lifetime Extension in Wireless Sensor Networks
Next Article in Special Issue
Skeleton-Based Abnormal Gait Detection
Previous Article in Journal
Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel
Previous Article in Special Issue
Sensor Fusion and Smart Sensor in Sports and Biomedical Applications
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(10), 1631; doi:10.3390/s16101631

Assessing Walking Strategies Using Insole Pressure Sensors for Stroke Survivors

1
Telematics Engineering Department, Universidad Carlos III de Madrid; Av. Universidad, 30, 28911 Leganes, Spain
2
School of Health and Related Research, University of Sheffield; Regent Court, 30, S1 4DA Sheffield, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Panicos Kyriacou
Received: 29 June 2016 / Revised: 16 September 2016 / Accepted: 27 September 2016 / Published: 1 October 2016
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [5630 KB, uploaded 1 October 2016]   |  

Abstract

Insole pressure sensors capture the different forces exercised over the different parts of the sole when performing tasks standing up such as walking. Using data analysis and machine learning techniques, common patterns and strategies from different users to achieve different tasks can be automatically extracted. In this paper, we present the results obtained for the automatic detection of different strategies used by stroke survivors when walking as integrated into an Information Communication Technology (ICT) enhanced Personalised Self-Management Rehabilitation System (PSMrS) for stroke rehabilitation. Fourteen stroke survivors and 10 healthy controls have participated in the experiment by walking six times a distance from chair to chair of approximately 10 m long. The Rivermead Mobility Index was used to assess the functional ability of each individual in the stroke survivor group. Several walking strategies are studied based on data gathered from insole pressure sensors and patterns found in stroke survivor patients are compared with average patterns found in healthy control users. A mechanism to automatically estimate a mobility index based on the similarity of the pressure patterns to a stereotyped stride is also used. Both data gathered from stroke survivors and healthy controls are used to evaluate the proposed mechanisms. The output of trained algorithms is applied to the PSMrS system to provide feedback on gait quality enabling stroke survivors to self-manage their rehabilitation. View Full-Text
Keywords: insole pressure sensors; stroke survivals; machine learning; rehabilitation; walking strategies insole pressure sensors; stroke survivals; machine learning; rehabilitation; walking strategies
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

Munoz-Organero, M.; Parker, J.; Powell, L.; Mawson, S. Assessing Walking Strategies Using Insole Pressure Sensors for Stroke Survivors. Sensors 2016, 16, 1631.

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