aceA protocol for validation of novel artificial intelligence-based framework for dyspnoea investigation with cardiopulmonary exercise testing
Background Exertional dyspnoea largely represents the sensory translation of an ever-growing dynamic mismatch between ventilatory demand and capacity as exercise intensifies. This fundamental tenet, however, has not been formally incorporated into data display and clinical interpretation of incremental cardiopulmonary exercise testing (CPET). The objectives of the present study were to validate a novel framework (Dynamic Assessment of Dyspnoea and Ventilation on Exercise (DyVe-X)) to quantify the severity of exe…
Protocol proposes AI-based DyVe-X software to continuously quantify exertional dyspnoea against work rate and ventilation and to identify excessive and constrained breathing patterns during incremental CPET, with anticipated superior performance over peak breathing reserve criterion.
Validation is limited to tobacco-exposed cohorts at risk for or with COPD, not a general dyspnoea population, and outcomes are presented as hypotheses rather than observed results.
Evidence
- Peer-reviewedERJ Open Research2026-09-07
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Truvace Impact Record TRV-2026-1033, v1: “A protocol for validation of novel artificial intelligence-based framework for dyspnoea investigation with cardiopulmonary exercise testing.” Truvace, 2026-09-09. /record/TRV-2026-1033 (accessed at citation time). sha256 36829714a930a296…
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