Development of a new submaximal walk test to predict maximal oxygen consumption in healthy adults

Hyuk In Yang, Wonhee Cho, Dong Hoon Lee, Sang Hoon Suh, Justin Y. Jeon

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The aim of the study was to develop a simple submaximal walk test protocol and equation using heart rate (HR) response variables to predict maximal oxygen consumption (VO2 max). A total of 60 healthy adults were recruited to test the validity of 3 min walk tests (3MWT). VO2 max and HR responses during the 3MWTs were measured. Multiple regression analysis was used to develop prediction equations. As a result, HR response variables including resting HR and HR during walking and recovery at two different cadences were significantly correlated with VO2 max. The equations developed using multiple regression analyses were able to predict VO2 max values (r = 0.75–0.84; r2 = 0.57–0.70; standard error of estimate (SEE) = 4.80–5.25 mL/kg/min). The equation that predicted VO2 max the best was at the cadence of 120 steps per minute, which included sex; age; height; weight; body mass index; resting HR; HR at 1 min, 2 min and 3 min; HR recovery at 1 min and 2 min; and other HR variables calculated based on these measured HR variables (r = 0.84; r2 = 0.70; SEE = 4.80 mL/kg/min). In conclusion, the 3MWT developed in this study is a safe and practical submaximal exercise protocol for healthy adults to predict VO2 max accurately, even compared to the well-established submaximal exercise protocols, and merits further investigation.

Original languageEnglish
Article number5726
JournalSensors
Volume21
Issue number17
DOIs
Publication statusPublished - 2021 Sept 1

Bibliographical note

Funding Information:
Funding: This work was supported by Samsung Electronics through Yonsei University (project number 2015-110-1098), the National Research Foundation of Korea (NRF-2015S1A5B8036349) and Yonsei Signature Research Cluster Program of 2021-22-0009.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Information Systems
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering
  • Biochemistry

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