Saudi Journal of Biological Sciences (Jun 2020)

Detection of ventilatory thresholds using near-infrared spectroscopy with a polynomial regression model

  • Chih-Wei Lin,
  • Chun-Feng Huang,
  • Jong-Shyan Wang,
  • Li-Lan Fu,
  • Tso-Yen Mao

Journal volume & issue
Vol. 27, no. 6
pp. 1637 – 1642

Abstract

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Whether near-infrared spectroscopy (NIRS) is a convenient and accurate method of determining first and second ventilatory thresholds (VT1 and VT2) using raw data remains unknown. This study investigated the reliability and validity of VT1 and VT2 determined by NIRS skeletal muscle hemodynamic raw data via a polynomial regression model. A total of 100 male students were recruited and performed maximal cycling exercises while their cardiopulmonary and NIRS muscle hemodynamic data were measured. The criterion validity of VT1VET and VT2VET were determined using a traditional V-slope and ventilatory efficiency. Statistical significance was set at α = . 05. There was high reproducibility of VT1NIRS and VT2NIRS determined by a NIRS polynomial regression model during exercise (VT1NIRS, r = 0.94; VT2NIRS, r = 0.93). There were high correlations of VT1VET vs VT1NIRS (r = 0.93, p < .05) and VT2VET vs VT2NIRS (r = 0.94, p < .05). The oxygen consumption (VO2) between VT1VET and VT1NIRS or VT2VET and VT2NIRS was not significantly different. NIRS raw data are reliable and valid for determining VT1 and VT2 in healthy males using a polynomial regression model. Skeletal muscle raw oxygenation and deoxygenation status reflects more realistic causes and timing of VT1 and VT2.

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