Related Experiment Video
Updated: Mar 24, 2026
Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
Estimation of Energy Expenditure for Wheelchair Users Using a Physical Activity Monitoring System
Shivayogi V Hiremath1, Stephen S Intille2, Annmarie Kelleher3
1Department of Veterans Affairs, Human Engineering Research Laboratories, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA; Department of Rehabilitation Science and Technology, University of Pittsburgh, Pittsburgh, PA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA; Department of Physical Therapy, Temple University, Philadelphia, PA.
Objective:
To develop and evaluate energy expenditure (EE) estimation models for a physical activity monitoring system (PAMS) in manual wheelchair users with spinal cord injury (SCI).
Design:
Cross-sectional study.
Setting:
University-based laboratory environment, a semistructured environment at the National Veterans Wheelchair Games, and the participants' home environments.
Participants:
Volunteer sample of manual wheelchair users with SCI (N=45).
Intervention:
Participants were asked to perform 10 physical activities (PAs) of various intensities from a list. The PAMS consists of a gyroscope-based wheel rotation monitor (G-WRM) and an accelerometer device worn on the upper arm or on the wrist. Criterion EE using a portable metabolic cart and raw sensor data from PAMS were collected during each of these activities.
Main Outcome Measures:
Estimated EE using custom models for manual wheelchair users based on either the G-WRM and arm accelerometer (PAMS-Arm) or the G-WRM and wrist accelerometer (PAMS-Wrist).
Results:
EE estimation performance for the PAMS-Arm (average error ± SD: -9.82%±37.03%) and PAMS-Wrist (-5.65%±32.61%) on the validation dataset indicated that both PAMS-Arm and PAMS-Wrist were able to estimate EE for a range of PAs with <10% error. Moderate to high intraclass correlation coefficients (ICCs) indicated that the EE estimated by PAMS-Arm (ICC3,1=.82, P<.05) and PAMS-Wrist (ICC3,1=.89, P<.05) are consistent with the criterion EE.
Conclusions:
Availability of PA monitors can assist wheelchair users to track PA levels, leading toward a healthier lifestyle. The new models we developed can estimate PA levels in manual wheelchair users with SCI in laboratory and community settings.
