Literature DB >> 19964247

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

Shivayogi V Hiremath1, Dan Ding.   

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 too- l to gauge their daily physical activity and EE.

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Year:  2009        PMID: 19964247     DOI: 10.1109/IEMBS.2009.5333626

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection.

Authors:  Gautam Thatte; Ming Li; Sangwon Lee; B Adar Emken; Murali Annavaram; Shrikanth Narayanan; Donna Spruijt-Metz; Urbashi Mitra
Journal:  IEEE Trans Signal Process       Date:  2011       Impact factor: 4.931

2.  Sensor Fusion to Infer Locations of Standing and Reaching Within the Home in Incomplete Spinal Cord Injury.

Authors:  Luca Lonini; Timothy Reissman; Jose M Ochoa; Chaithanya K Mummidisetty; Konrad Kording; Arun Jayaraman
Journal:  Am J Phys Med Rehabil       Date:  2017-10       Impact factor: 2.159

3.  Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Authors:  Tom Edward Nightingale; Jean-Philippe Walhin; Dylan Thompson; James Lee John Bilzon
Journal:  PLoS One       Date:  2015-05-08       Impact factor: 3.240

4.  Classification of Wheelchair Related Shoulder Loading Activities from Wearable Sensor Data: A Machine Learning Approach.

Authors:  Wiebe H K de Vries; Sabrina Amrein; Ursina Arnet; Laura Mayrhuber; Cristina Ehrmann; H E J Veeger
Journal:  Sensors (Basel)       Date:  2022-09-29       Impact factor: 3.847

  4 in total

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