Table of Contents
ISRN Biomedical Engineering
Volume 2013 (2013), Article ID 908452, 10 pages
http://dx.doi.org/10.1155/2013/908452
Research Article

Ambulatory Monitoring of Physical Activity Based on Knee Flexion/Extension Measured by Inductive Sensor Technology

1MOBILAB, Thomas More Kempen/KU Leuven, Kleinhoefstraat 4, 2440 Geel, Belgium
2Faculty of Health Medicine and Life Sciences, Maastricht University Medical Centre, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
3TNO Medical Devices, De Rondom 1, 5600 HE Eindhoven, The Netherlands
4ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium
5iMinds Future Health Department, Kasteelpark Arenberg 10, Box 2446, 3001 Leuven, Belgium

Received 28 March 2013; Accepted 19 May 2013

Academic Editors: S. Hirokawa and B. J. Roth

Copyright © 2013 Bert Bonroy et al. 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.

Abstract

We developed a knee brace to measure the knee angle and implicitly the flexion/extension (f/e) of the knee joint during daily activities. The goal of this study is to classify and validate a limited set of physical activities on ten young healthy subjects based on knee f/e. Physical activities included in this study are walking, ascending and descending of stairs, and fast locomotion (such as jogging, running, and sprinting) at self-selected speeds. The knee brace includes 2 accelerometers for static measurements and calibration and an inductive sensor for dynamic measurements. As we focus on physical activities, the inductive sensor will provide the required information on knee f/e. In this study, the subjects traversed a predefined track which consisted of indoor paths, outdoor paths, and obstacles. The activity classification algorithm based on peak detection in the knee f/e angle resulted in a detection rate of 95.9% for walking, 90.3% for ascending stairs, 78.3% for descending stairs, and 82.2% for fast locomotion. We conclude that we developed a measurement device which allows long-term and ambulatory monitoring. Furthermore, it is possible to predict the aforementioned activities with an acceptable performance.