AI Article Synopsis

  • Accurately measuring physical activity and energy expenditure in wheelchair users with chronic disabilities is difficult due to limited understanding of measurement tools and techniques.
  • The 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) shows the best reliability among self-report methods, but its complexity and recall bias are concerns.
  • Objective tools like accelerometers are more reliable for measurement, especially when worn on the arm or wrist, yet further advanced data analysis and multi-sensor devices could enhance energy expenditure predictions for complex movements.

Article Abstract

Accurately measuring physical activity and energy expenditure in persons with chronic physical disabilities who use wheelchairs is a considerable and ongoing challenge. Quantifying various free-living lifestyle behaviours in this group is at present restricted by our understanding of appropriate measurement tools and analytical techniques. This review provides a detailed evaluation of the currently available measurement tools used to predict physical activity and energy expenditure in persons who use wheelchairs. It also outlines numerous considerations specific to this population and suggests suitable future directions for the field. Of the existing three self-report methods utilised in this population, the 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) telephone interview demonstrates the best reliability and validity. However, the complexity of interview administration and potential for recall bias are notable limitations. Objective measurement tools, which overcome such considerations, have been validated using controlled laboratory protocols. These have consistently demonstrated the arm or wrist as the most suitable anatomical location to wear accelerometers. Yet, more complex data analysis methodologies may be necessary to further improve energy expenditure prediction for more intricate movements or behaviours. Multi-sensor devices that incorporate physiological signals and acceleration have recently been adapted for persons who use wheelchairs. Population specific algorithms offer considerable improvements in energy expenditure prediction accuracy. This review highlights the progress in the field and aims to encourage the wider scientific community to develop innovative solutions to accurately quantify physical activity in this population.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5332318PMC
http://dx.doi.org/10.1186/s40798-017-0077-0DOI Listing

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