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International Journal of Telemedicine and Applications
Volume 2011 (2011), Article ID 671040, 18 pages
Research Article

Experience with Using the Sensewear BMS Sensor System in the Context of a Health and Wellbeing Application

1Telemedicine Group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Zuidhorst building, P.O. Box 217, 7500 AE Enschede, The Netherlands
2Consumer Science & Intelligent Systems, Food & Biobased Research, WUR, 6700 AA Wageningen, The Netherlands
3Cluster Non-Invasive Neuromuscular Assessment (NINA), Roessingh Research and Development, P.O. Box 310, 7500 AH Enschede, The Netherlands

Received 29 September 2010; Revised 31 January 2011; Accepted 17 February 2011

Academic Editor: E. A. Krupinski

Copyright © 2011 Val Jones 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.


An assessment of a sensor designed for monitoring energy expenditure, activity, and sleep was conducted in the context of a research project which develops a weight management application. The overall goal of this project is to affect sustainable behavioural change with respect to diet and exercise in order to improve health and wellbeing. This paper reports results of a pretrial in which three volunteers wore the sensor for a total of 11 days. The aim was to gain experience with the sensor and determine if it would be suitable for incorporation into the ICT system developed by the project to be trialled later on a larger population. In this paper we focus mainly on activity monitoring and user experience. Data and results including visualizations and reports are presented and discussed. User experience proved positive in most respects. Exercise levels and sleep patterns correspond to user logs relating to exercise sessions and sleep patterns. Issues raised relate to accuracy, one source of possible interference, the desirability of enhancing the system with real-time data transmission, and analysis to enable real-time feedback. It is argued that automatic activity classification is needed to properly analyse and interpret physical activity data captured by accelerometry.