Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form
D-Scholarship @ Pitt Banner and Links to Homepage

Evaluation of activity monitors to estimate energy expenditure in manual wheelchair users

Hiremath, SV and Ding, D (2009) Evaluation of activity monitors to estimate energy expenditure in manual wheelchair users. Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009. 835 - 838.

[img] Plain Text (licence)
Available under License : See the attached license file.
Download (1kB)

Abstract

In an effort to make activity monitors usable by manual wheelchair users with Spinal Cord Injury (SCI), our study examines the validity of SenseWear® Armband (SenseWear) and RT3 in assessing energy expenditure (EE) during wheelchair related activities. This paper presents the data obtained from six subjects (n=6) with SCI performing three activities, including wheelchair propulsion, armergometer exercise and deskwork. The analysis presented here compares the EE estimated from the SenseWear and the RT3 with respect to the EE measured from a portable metabolic cart. It was found that the SenseWear overestimated EE for resting (+5.78%), wheelchair propulsion (+88.20%, +46.20%, and +138.21% for the three trials at different intensities, respectively), arm-ergometer exercise (+55.05%, +26.91%, and +39.17% for the three trials at different intensities, respectively) and deskwork (+13.11%). The results also indicate that RT3 underestimated EE for resting (-3.06%), wheelchair propulsion (-24.23%, -19.42%, and -9.98% for the three trials at different intensities, respectively), arm-ergometer exercise (-49.06%, -53.69% and -52.08 for the three trials at different intensities, respectively) and measured EE relatively accurate for deskwork. Good and moderate Intraclass correlations were found between EE measured by metabolic cart and EE estimated by SenseWear (0.787, p<0.0001) and RT3 (0.705, p<0.0001). Weka, machine learning software, was used to select attributes and model EE equations for the SenseWear and the RT3. Excellent and good Intraclass correlations were found between the EE measured by the metabolic cart and the estimated EE based on the models for SenseWear (0.944, p<0.0001) and RT3 (0.821, p<0.0001). Future work will test more subjects to refine the model and provide manual wheelchair users with a valid tool to gauge their daily physical activity and EE. ©2009 IEEE.

Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Hiremath, SVsvh4@pitt.eduSVH4
Ding, Ddad5@pitt.eduDAD5
Centers: Other Centers, Institutes, Offices, or Units > Human Engineering Research Laboratories
Date: 1 January 2009
Date Type: Publication
Journal or Publication Title: Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Page Range: 835 - 838
DOI or Unique Handle: 10.1109/iembs.2009.5333626
Schools and Programs: School of Health and Rehabilitation Sciences > Rehabilitation Science and Technology
Refereed: No
MeSH Headings: Actigraphy--instrumentation; Energy Metabolism; Equipment Design; Equipment Failure Analysis; Humans; Monitoring, Ambulatory--methods; Motor Activity; Reproducibility of Results; Sensitivity and Specificity; Spinal Cord Injuries--physiopathology; Spinal Cord Injuries--rehabilitation; Wheelchairs
PubMed ID: 19964247
Date Deposited: 30 Jan 2013 20:57
Last Modified: 02 Feb 2019 14:55
URI: http://d-scholarship-dev.library.pitt.edu/id/eprint/17159

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item