Next Article in Journal
Various On-Chip Sensors with Microfluidics for Biological Applications
Next Article in Special Issue
Novel Wearable and Wireless Ring-Type Pulse Oximeter with Multi-Detectors
Previous Article in Journal
Reliable Adaptive Data Aggregation Route Strategy for a Trade-off between Energy and Lifetime in WSNs
Previous Article in Special Issue
DIMETER: A Haptic Master Device for Tremor Diagnosis in Neurodegenerative Diseases
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(9), 16994-17007; doi:10.3390/s140916994

Evaluation of Two Approaches for Aligning Data Obtained from a Motion Capture System and an In-Shoe Pressure Measurement System

1
Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA 24061, USA
2
Virginia Tech–Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, VA 24061, USA
*
Author to whom correspondence should be addressed.
Received: 10 July 2014 / Revised: 13 August 2014 / Accepted: 11 September 2014 / Published: 12 September 2014
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [2636 KB, uploaded 12 September 2014]   |  

Abstract

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To use an IPM system along with a motion capture system, there is thus a need to align the coordinate systems of the two measurement systems. To address this need, the current study examined two different approaches—rigid body transformation and nonlinear mapping (i.e., multilayer feed-forward neural network (MFNN))—to express COP measurements from an IPM system in the coordinate system of a motion capture system. Ten participants (five male and five female) completed several simulated manual material handling (MMH) activities, and during these activities the performance of the two approaches was assessed. Results indicated that: (1) performance varied between MMH activity types; and (2) a MFNN performed better than or comparable to the rigid body transformation, depending on the specific input variable sets used. Further, based on the results obtained, it was argued that a nonlinear mapping vs. rigid body transformation approach may be more effective to account for shoe deformation during MMH or potentially other types of physical activity. View Full-Text
Keywords: in-shoe pressure measurement; center of pressure; manual material handling in-shoe pressure measurement; center of pressure; manual material handling
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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

Kim, S.; Nussbaum, M.A. Evaluation of Two Approaches for Aligning Data Obtained from a Motion Capture System and an In-Shoe Pressure Measurement System. Sensors 2014, 14, 16994-17007.

Show more citation formats Show less citations formats

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