Literature DB >> 25134004

Predicting physical activity energy expenditure in manual wheelchair users.

Tom Edward Nightingale1, Jean-Philippe Walhim, Dylan Thompson, James L J Bilzon.   

Abstract

PURPOSE: This study aimed to assess the influence of anatomical placement of an accelerometer on physical activity energy expenditure prediction in manual wheelchair users.
METHODS: Ten accelerometer units (ActiGraph GT3X+) were attached to a multiaxis shaker table and subjected to a sinusoidal oscillation procedure to assess mechanical validity and reliability. Fifteen manual wheelchair users (mean ± SD: age, 36 ± 11 yr; body mass, 70 ± 12 kg) then completed five activities, including desk work and wheelchair propulsion (2, 4, 6, and 8 km·h). Expired gases were collected throughout. GT3X+ accelerometers were worn on the right wrist, upper arm, and waist. The relations between physical activity counts and metabolic rate were subsequently assessed, and bias ± 95% limits of agreement was calculated.
RESULTS: During mechanical testing, coefficients of variation ranged from 0.2% to 4.7% (intraunit) and 0.9% to 5.2% (interunit) in all axes. During human exercise testing, physical activity counts at each anatomical location was significantly (P < 0.01) correlated with metabolic rate (wrist, r = 0.93; upper arm, r = 0.87; waist, r = 0.73). The SEE for each correlation were 3.34, 4.38, and 6.07 kJ·min for the wrist, upper arm, and waist, respectively. The absolute bias ± 95% limits of agreement values were 0.0 ± 6.5 kJ·min, 0.0 ± 8.5 kJ·min, and 0.0 ± 11.8 kJ·min for the wrist, upper arm, and waist, respectively.
CONCLUSIONS: The ActiGraph GT3X+ is a reliable tool for determining mechanical movements within the physiological range of human movement. Of the three anatomical locations considered, a wrist-mounted accelerometer explains more of the variance and results in the lowest random error when predicting physical activity energy expenditure in manual wheelchair users.

Entities:  

Mesh:

Year:  2014        PMID: 25134004     DOI: 10.1249/MSS.0000000000000291

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  15 in total

1.  Accelerometer output and its association with energy expenditure during manual wheelchair propulsion.

Authors:  Y C Learmonth; D Kinnett-Hopkins; I M Rice; J L Dysterheft; R W Motl
Journal:  Spinal Cord       Date:  2015-03-17       Impact factor: 2.772

Review 2.  Data logger technologies for manual wheelchairs: A scoping review.

Authors:  François Routhier; Josiane Lettre; William C Miller; Jaimie F Borisoff; Kate Keetch; Ian M Mitchell; CanWheel Research Team
Journal:  Assist Technol       Date:  2017-01-04

3.  Measuring Physical Activity in Spinal Cord Injury Using Wrist-Worn Accelerometers.

Authors:  Susan L Murphy; Anna L Kratz; Aaron J Zynda
Journal:  Am J Occup Ther       Date:  2019 Jan/Feb

4.  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

5.  Predicting physical activity energy expenditure in wheelchair users with a multisensor device.

Authors:  T E Nightingale; J P Walhin; D Thompson; J L J Bilzon
Journal:  BMJ Open Sport Exerc Med       Date:  2015-08-13

6.  The Smartphone Peer Physical Activity Counseling (SPPAC) Program for Manual Wheelchair Users: Protocol of a Pilot Randomized Controlled Trial.

Authors:  Krista L Best; François Routhier; Shane N Sweet; Kelly P Arbour-Nicitopoulos; Jaimie F Borisoff; Luc Noreau; Kathleen A Martin Ginis
Journal:  JMIR Res Protoc       Date:  2017-04-26

Review 7.  Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions.

Authors:  Tom E Nightingale; Peter C Rouse; Dylan Thompson; James L J Bilzon
Journal:  Sports Med Open       Date:  2017-03-01

8.  Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors.

Authors:  Enhad A Chowdhury; Max J Western; Thomas E Nightingale; Oliver J Peacock; Dylan Thompson
Journal:  PLoS One       Date:  2017-02-24       Impact factor: 3.240

9.  Is Fitbit Charge 2 a feasible instrument to monitor daily physical activity and handbike training in persons with spinal cord injury? A pilot study.

Authors:  M C Maijers; O Verschuren; J M Stolwijk-Swüste; C F van Koppenhagen; S de Groot; M W M Post
Journal:  Spinal Cord Ser Cases       Date:  2018-09-11

10.  Push-Rate Threshold for Physical Activity Intensity in Persons Who Use Manual Wheelchairs.

Authors:  Ian M Rice; Brenda Jeng; Stephanie L Silveira; Robert W Motl
Journal:  Am J Phys Med Rehabil       Date:  2021-03-01       Impact factor: 3.412

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