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

AIM: To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. METHODS: 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activiti...

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Autores principales: Nightingale, T E, Walhin, J P, Thompson, D, Bilzon, J L J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5117017/
https://www.ncbi.nlm.nih.gov/pubmed/27900111
http://dx.doi.org/10.1136/bmjsem-2015-000008
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author Nightingale, T E
Walhin, J P
Thompson, D
Bilzon, J L J
author_facet Nightingale, T E
Walhin, J P
Thompson, D
Bilzon, J L J
author_sort Nightingale, T E
collection PubMed
description AIM: To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. METHODS: 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE. RESULTS: Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and −0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC. SUMMARY: PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE.
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spelling pubmed-51170172016-11-29 Predicting physical activity energy expenditure in wheelchair users with a multisensor device Nightingale, T E Walhin, J P Thompson, D Bilzon, J L J BMJ Open Sport Exerc Med Research AIM: To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. METHODS: 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE. RESULTS: Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and −0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC. SUMMARY: PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE. BMJ Publishing Group 2015-08-13 /pmc/articles/PMC5117017/ /pubmed/27900111 http://dx.doi.org/10.1136/bmjsem-2015-000008 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Research
Nightingale, T E
Walhin, J P
Thompson, D
Bilzon, J L J
Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title_full Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title_fullStr Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title_full_unstemmed Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title_short Predicting physical activity energy expenditure in wheelchair users with a multisensor device
title_sort predicting physical activity energy expenditure in wheelchair users with a multisensor device
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5117017/
https://www.ncbi.nlm.nih.gov/pubmed/27900111
http://dx.doi.org/10.1136/bmjsem-2015-000008
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