Related Experiment Video
Updated: May 21, 2026

Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise
Published on: December 19, 2024
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.
Abstract:
A ubiquitously available and accurate non-invasive ventilatory threshold assessment (NIVA) would substantially improve real-world performance assessment evaluation in both clinical and elite sports settings. We hypothesised that ECG-derived ventilatory phase analysis achieves reference-standard accuracy for second ventilatory threshold (VT2) determination. 74 healthy adults performed stepwise cardiopulmonary exercise testing with simultaneous lactate sampling to retrieve VT2 and lactate-based (Dmax; LT2) thresholds. Threshold agreement was evaluated for heart rate (HR) and exercise load (W) between VT2, LT2, age-estimated HR (HR-Est) and NIVA. In 66 assessable datasets, NIVA and VT2 yielded equivalent threshold estimates for HR (- 0.46 bpm; 90% CI [- 2.10;1.17]) and exercise load (0.46 W; 90% CI [- 2.35; 3.27]). VT2 and HR-Est diverged (HR - 7.22 bpm, p < 0.001; load - 6.26 W; p < 0.001). LT2 was available in 58 subjects and differed from both VT2 (p < 0.001) and NIVA (p < 0.001). Correlations supported these findings, with close associations between VT2 and NIVA (HR r = 0.84; load r = 0.96). NIVA derived a high-intensity performance threshold from ECG signals with reference-standard fidelity and showed close agreement with CPET-derived VT2. Its performance and accessibility make it attractive for frequent reassessment of a VT2-aligned threshold without the need for spiroergometry or lactate measurements. Validation across devices, protocols, populations, and real-world signal conditions is warranted.
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