Original article
Predicting Energy Expenditure of Manual Wheelchair Users With Spinal Cord Injury Using a Multisensor-Based Activity Monitor

https://doi.org/10.1016/j.apmr.2012.05.004Get rights and content

Abstract

Hiremath SV, Ding D, Farringdon J, Cooper RA. Predicting energy expenditure of manual wheelchair users with spinal cord injury using a multisensor-based activity monitor.

Objective

To develop and evaluate new energy expenditure (EE) prediction models for manual wheelchair users (MWUs) with spinal cord injury (SCI) based on a commercially available multisensor-based activity monitor.

Design

Cross-sectional.

Setting

Laboratory.

Participants

Volunteer sample of MWUs with SCI (N=45).

Intervention

Subjects were asked to perform 4 activities including resting, wheelchair propulsion, arm-ergometer exercise, and deskwork. Criterion EE using a metabolic cart and raw sensor data from a multisensor activity monitor was collected during each of these activities.

Main Outcome Measures

Two new EE prediction models including a general model and an activity-specific model were developed using enhanced all-possible regressions on 36 MWUs and tested on the remaining 9 MWUs.

Results

The activity-specific and general EE prediction models estimated the EE significantly better than the manufacturer's model. The average EE estimation error using the manufacturer's model and the new general and activity-specific models for all activities combined was –55.31% (overestimation), 2.30% (underestimation), and 4.85%, respectively. The average EE estimation error using the manufacturer's model, the new general model, and activity-specific models for various activities varied from –19.10% to –89.85%, –18.13% to 25.13%, and –4.31% to 9.93%, respectively.

Conclusions

The predictors for the new models were based on accelerometer and demographic variables, indicating that movement and subject parameters were necessary in estimating the EE. The results indicate that the multisensor activity monitor with new prediction models can be used to estimate EE in MWUs with SCI during wheelchair-related activities mentioned in this study.

Section snippets

Methods

This study took place at a university-based research facility. The institutional review board at the university approved the study.

Results

Demographic characteristics of the subjects are described in table 1. All the subjects completed the 8 activity trials. Because of device malfunction of the K4b2, 3 trials from 3 subjects had to be discarded. In addition, 5 trials from 4 subjects that did not yield steady-state conditions were also discarded.

The general model shown in equation 1 takes all the 4 activities into consideration. The activity-specific models are shown in (2), (3), (4), (5). Table 2 lists the predictors selected for

Discussion

Research has shown that off-the-shelf activity monitors cannot accurately predict EE in MWUs with SCI.6, 10 Our previous study6 using SenseWear has found large EE estimation errors ranging from 24.4% to 125.8% among 24 MWUs with SCI. Davis10 showed that the mean signed EE by SenseWear (14.3±6.0kJ/min) was much higher than the EE from a metabolic cart (11.4±4.0kJ/min) during wheelchair propulsion on a treadmill. This study with a larger cohort also showed a consistent trend of large EE

Conclusions

In this study, we have developed and evaluated new EE prediction models for MWUs with SCI based on a popular commercially available activity monitor. To our knowledge, this is the first study to develop new EE prediction models for this population based on the SenseWear activity monitor. The new models developed here can be used in clinical applications of using SenseWear activity monitors to estimate EE for MWUs with SCI during the wheelchair-related activities discussed in this study. We

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    Results from phase 2 indicated that the most commonly used tool to measure PA in individuals with an SCI was the accelerometer. Other tools included heart rate monitors,41 pedometers,42,43 and accelerometers and gyrometers.41,44,45 The Physical Activity Recall Assessment for Individuals with Spinal Cord Injuries46,47 was the most frequently tested assessment, along with the Leisure Time Physical Activity Questionnaire48 and the Physical Activity Scale for Individuals with a Physical Disability.49,50

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Supported by the Rehabilitation Engineering Research Center on Interactive Exercise Technologies and Exercise Physiology for Persons with Disabilities (grant no. H133E070029), funded by the National Institute on Disability and Rehabilitation Research; and by the VA Center of Excellence for Wheelchairs and Associated Rehabilitation Engineering (grant no. B3142C). The contents do not represent the views of the Department of Veterans Affairs or the United States Government.

No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. Farringdon is employed by BodyMedia Inc, manufacturer of the SenseWear.

Reprints are not available from the author.

In-press corrected proof published online on Jul 6, 2012, at www.archives-pmr.org.

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