Predicting physical activity energy expenditure in wheelchair users with a multi-sensor device: Predicting energy expenditure in wheelchair users

Research output: Contribution to journalArticle

16 Citations (Scopus)
103 Downloads (Pure)

Abstract

Aim To assess the error in predicting physical activity energy expenditure (PAEE), using a multi-sensor device, in wheelchair users and to examine the efficacy of using an individual heart rate calibration method. Methods Fifteen manual wheelchair users (36 ± 10 years, 72 ± 11 kg) completed ten activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4 km·hr-1 (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 (ActiheartTM). Participants also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the ActiheartTM for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the ActiheartTM using manufacturer’s proprietary algorithms (group calibration; GC) or individual heart rate calibration (IC). Bland-Altman plots were used and mean absolute error 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 kcal·min-1 and -0.22 ± 0.96 kcal·min-1 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 individual heart rate calibration. Inter-individual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an individual heart rate calibration when using the ActiheartTM to predict PAEE.
Original languageEnglish
Pages (from-to)1- 8
Number of pages8
JournalBMJ Open Sport & Exercise Medicine
Volume1
Issue number1
DOIs
Publication statusPublished - 13 Aug 2015

Fingerprint Dive into the research topics of 'Predicting physical activity energy expenditure in wheelchair users with a multi-sensor device: Predicting energy expenditure in wheelchair users'. Together they form a unique fingerprint.

  • Cite this