
Loading, please wait...

Loading, please wait...

Accurate exercise threshold monitoring is essential for athletes and coaches to optimize training zones and improve performance. Traditionally, the gold-standard ventilatory thresholds require complex, breath-by-breath gas analysis. However, researchers are increasingly exploring Muscle Near-Infrared Spectroscopy (NIRS) and Heart Rate Variability (HRV) as non-invasive and more accessible alternatives. A recent study compared these diverse methods during maximal incremental cycling tests to determine their practical utility in clinical and sports settings.
Furthermore, the study involved 20 trained male cyclists who underwent a maximal incremental cycling test with continuous physiological recording. Analysts identified the first and second ventilatory thresholds (VT1 and VT2) and compared them to NIRS-derived and HRV-derived markers. Results showed no significant differences between group means for several parameters, such as oxygenated hemoglobin and specific HRV indices like SD1 and SD2. Consequently, these methods appear promising for identifying general physiological transitions within a group of athletes.
Despite the similar group averages, the agreement analysis revealed substantial inter-individual errors. In fact, the limits of agreement reached up to ±107 W, which significantly exceeds the standard 25 W incremental stage used in the testing protocol. Therefore, while these non-invasive tools provide valuable physiological data, they currently lack the precision required for specific individual training prescription. Athletes and clinicians should use NIRS and HRV as complements rather than absolute substitutes for standard ventilatory thresholds.
NIRS measures muscle oxygenation and deoxygenation levels. This technology helps identify metabolic transition points where oxygen demand begins to exceed supply during increasing exercise intensities.
While group averages may align well, substantial inter-individual variability and measurement errors limit the precision of HRV thresholds for individual athletes. This makes them less reliable for precise personal training prescriptions.
Disclaimer: This content is for informational and educational purposes only. It does not constitute professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition. Refer to the latest local and national guidelines for clinical practice.
References

Read summarized clinical updates, watch expert medical content, and earn CME certifications right from your smartphone.


A study evaluates if NIRS and HRV can accurately replace ventilatory thresholds for identifying training zones, finding significant inter-individual variati...
6 months ago

A retrospective cohort study reveals that frailty quadruples the odds of pressure injuries in hospitalized older adults. Integrating the Clinical Frailty Scale with comprehensive geriatric care is crucial for identifying vulnerability early and implementing targeted multidisciplinary prevention.
Today

Occult maternal malignancy accounts for 3.82% of persistent unreportable NIPT results with genomic noise. Multiple chromosomal aberrations, notably on chromosome 18, warrant thorough oncological evaluation and whole-body MRI to ensure timely maternal diagnosis while preserving fetal care.
Today

This article reviews the forensic and clinical complexities of acute myocarditis arising on left ventricular hypertrophy in children, highlighting early diagnostic red flags and multidisciplinary postmortem autopsy protocols.
Today

A randomized controlled trial demonstrates that an eight-week dual-task training intervention significantly improves static and dynamic postural control over standard balance exercises in individuals with chronic ankle instability, addressing critical neurocognitive deficits during athletic and daily activities.
Today

A retrospective cohort study of 7,716 ICU patients from the MIMIC-IV database demonstrates that Gradient Boosting Decision Trees significantly outperform traditional SOFA scores in predicting in-hospital mortality among patients with sepsis and diabetes, with SHAP analysis providing clinical interpretability.
Today