EE_estimator is a computer application designed for estimating energy expenditure of manual wheelchair users with spinal cord injury (SCI) using the commercial activity monitor SenseWear armband (Bodymedia, Inc., Pittsburgh, PA). This application uses the personal information (e.g., height and weight) of a manual wheelchair user with SCI, along with the raw data collected by the SenseWear armband to provide a more accurate estimate of his/her energy expenditure as compared to the default outputs from the SenseWear armband. In order to use this application, you should have access to the raw data collected by the SenseWear armband typically through the SenseWear Professional Software.
Why is EE_estimator developed?
The SenseWear armband was originally designed for estimating physical activity and energy expenditure of the ambulatory population. Research has shown that the SenseWear armband is not accurate at tracking physical activity and energy expenditure in manual wheelchair users with SCI (1, 2). Therefore, our research team has created this application that uses custom models for manual wheelchair users with SCI derived from our research (3) to enable people who are interested in using SenseWear armbands for wheelchair users to obtain an accurate estimate of energy expenditure.
How was this application developed?
Our research team has developed two types of custom energy expenditure models, i.e. the general and the activity-specific models. The general model can be used when you do not have a log of activities performed by the wheelchair user. The activity-specific model can be used for four activities including resting while seated, light-weight deskwork (e.g., computer operation, reading etc.), wheelchair propulsion, and arm-ergometry exercise. Both models were developed using data collected from 45 manual wheelchair users with SCI. Participants were asked to wear a SenseWear armband and a portable metabolic cart (gas analyzer) while performing the four activities mentioned above in the laboratory setting. More details about the modeling process can be found in (3).
How accurate is this application?
We evaluated the two custom models with another group of 45 manual wheelchair users with spinal cord injury who performed a wide range of lifestyle and sporting based activities in both laboratory and home/community settings. Eighteen out of the 45 wheelchair users have participated in our previous study mentioned above. Overall, the general model has an average percent error of -2.8±26.1%, while the activity-specific model has an average percent error of -4.8±25.4% when compared to the portable metabolic cart readings. More information on the validity study can be found in (4, 5). It should be noted that both models were developed and tested among manual wheelchair users with SCI. We do not know how the models will perform when they are applied to manual wheelchair users with other diagnoses.
For more information on activity monitors for physical asssessment of wheelchair users, check out the projects page.
If you are interested in using the EE_estimator application, please share your project information as well as your contact information with us. We will follow up with you and send you the application. If you have any questions about using this application, please free feel to contact the Project Director Dr. Dan Ding at email@example.com. This work is supported by the RERC on Interactive Exercise Technologies and Exercise Physiology for Persons with Disabilities (#H133E120005) funded by the National Institute on Disability and Rehabilitation Research (NIDRR). The work is also supported by the Human Engineering Research Laboratories, VA Pittsburgh Healthcare System. The contents do not represent the views of the Department of Veterans Affairs or the United States Government.
- Hiremath S, Ding D. Evalution of activity monitors in manual wheelchair users with paraplegia. Journal of Spinal Cord Medicine. 2011;34(1):110-7. doi: 10.1179/107902610X12911165975142.
- Hiremath SV, Ding D, Evaluation of Activity Monitors in Estimating Energy Expenditure in Manual Wheelchair Users. RESNA Annual Conference; 2010; Las Vegas, Nevada.
- Hiremath S, Ding D, Farringdon J, Cooper RA. Predicting Energy Expenditure of Manual Wheelchair Users with Spinal Cord Injury Using a Multisensor-Based Activity Monitor. Achives of Physical Medicine and Rehabilitation. 2012;93(11):1937-43. doi: 10.1016/j.ampr.2012.05.004.
- Tsang KL, Hiremath SV, Ding D. Evaluating the Energy Expenditure Prediction Models for Manual Wheelchair Users with Spinal Cord Injuries. RESNA Annual Conference; Indianopolis, Indiana2014.
- Tsang KL, Hiremath SV, Ding D. Evaluation of the Energy Expenditure Prediction Models for Tracking Physical Activity in Manual Wheelchair Users. Journal of Rehabilitation Research & Development. 2014; In Review.