A Practical Cardiovascular Health Assessment for Manual Wheelchair Users During the 6-Minute Push Test

Traditional VO<sub>2max</sub> testing methods are often impractical for manual wheelchair users, as they rely on lower-body exercise protocols, require specialized equipment, and trained personnel. The 6-Minute Push Test (6MPT) is a widely used cardiovascular assessment that may provide...

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Bibliographic Details
Main Authors: Maja Goršič, Madisyn R. Adelman, Grace McClatchey, Jacob R. Rammer
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/7/2313
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Summary:Traditional VO<sub>2max</sub> testing methods are often impractical for manual wheelchair users, as they rely on lower-body exercise protocols, require specialized equipment, and trained personnel. The 6-Minute Push Test (6MPT) is a widely used cardiovascular assessment that may provide a feasible alternative for estimating aerobic capacity in this population. This study aimed to develop a predictive model for VO<sub>2max</sub> using physiological variables recorded during the 6MPT. Twenty-eight participants (14 novice and 14 expert manual wheelchair users) completed the test while wearing a VO<sub>2</sub> mask and heart rate monitor. Spearman correlation analysis showed that distance covered during the 6MPT significantly correlated with VO<sub>2max</sub> (r = 0.685, <i>p</i> < 0.001). A stepwise linear regression identified two predictive models: one using distance alone (R<sup>2</sup> = 0.416, <i>p</i> < 0.001) and another incorporating both distance and maximum heart rate (R<sup>2</sup> = 0.561, <i>p</i> < 0.001). These models offer practical estimations of VO<sub>2max</sub>, eliminating separate protocols. Our findings suggest that the 6MPT can serve as a simple, cost-effective alternative to laboratory-based VO<sub>2</sub> testing, facilitating routine cardiovascular fitness assessments for manual wheelchair users in clinical and community settings. Future research should focus on validating these models in a larger, more diverse cohort to enhance their generalizability.
ISSN:1424-8220