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Related Concept Videos

Electrocardiogram01:29

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Related Experiment Video

Updated: May 21, 2026

Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise
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Unlocking high-intensity performance thresholds through ventilatory signatures in the ECG.

V Heinz1,2, N Pilz3, L Fesseler2

  • 1Institute of Integrative NeuroAnatomy, Charité - University Medicine Berlin, Berlin, Germany.

Scientific Reports
|May 19, 2026
PubMed
Summary

Non-invasive ventilatory threshold assessment (NIVA) using ECG accurately determines the second ventilatory threshold (VT2). This accessible method offers reliable performance evaluation without spiroergometry or lactate testing.

Keywords:
Cardiopulmonary exercise testingECG-derived respirationExercise intensity assessmentPerformance thresholdsVentilatory threshold

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Area of Science:

  • Exercise Physiology
  • Cardiopulmonary Exercise Testing
  • Biomedical Engineering

Background:

  • Accurate non-invasive ventilatory threshold assessment (NIVA) is crucial for evaluating performance in clinical and sports settings.
  • Current methods for determining the second ventilatory threshold (VT2) often require invasive or complex procedures like spiroergometry or lactate sampling.
  • Developing a widely accessible and accurate NIVA method is a significant unmet need.

Purpose of the Study:

  • To investigate the accuracy of ECG-derived ventilatory phase analysis for determining the second ventilatory threshold (VT2).
  • To compare the NIVA-derived threshold with traditional methods, including VT2 from cardiopulmonary exercise testing (CPET) and lactate-based thresholds (LT2).
  • To assess the agreement between NIVA and VT2 for heart rate (HR) and exercise load (W).

Main Methods:

  • Seventy-four healthy adults underwent stepwise CPET with simultaneous lactate sampling.
  • The second ventilatory threshold (VT2) and lactate-based thresholds (LT2) were determined.
  • ECG-derived ventilatory phase analysis (NIVA) was employed to estimate the ventilatory threshold, and results were compared with VT2, LT2, and age-estimated HR (HR-Est).

Main Results:

  • NIVA demonstrated high accuracy, yielding threshold estimates for HR and exercise load that closely agreed with CPET-derived VT2 (HR: -0.46 bpm; Load: 0.46 W).
  • Significant differences were observed between VT2 and HR-Est (HR: -7.22 bpm; Load: -6.26 W).
  • LT2, available in 58 subjects, differed significantly from both VT2 and NIVA (p < 0.001).

Conclusions:

  • ECG-derived NIVA provides a non-invasive method for determining a high-intensity performance threshold with reference-standard fidelity, closely matching CPET-derived VT2.
  • NIVA's performance and accessibility make it a valuable tool for frequent performance reassessment without the need for spiroergometry or lactate measurements.
  • Further validation of NIVA across diverse devices, protocols, populations, and real-world conditions is warranted.