A UK pilot study explored whether physical activity data from wearable devices and a smartphone app (My Heart Counts) could help detect idiopathic pulmonary arterial hypertension (IPAH) earlier, before formal diagnosis. Analysing up to eight years of real-world activity and heart rate data from 109 participants, including patients with idiopathic pulmonary arterial hypertension, disease controls, and healthy individuals, a machine learning classifier distinguished idiopathic pulmonary arterial hypertension patients from healthy individuals and disease controls with strong accuracy (AUC 0.87), rising to 0.94 when combined with in-app questionnaire responses. Validation in a US cohort showed promising but more modest results (AUC 0.74). Wearable metrics also correlated with the standard six-minute walk distance test. The authors conclude that digital health tools could complement traditional methods for earlier detection and remote monitoring of idiopathic pulmonary arterial hypertension, with larger studies now warranted.
Read more at this link on the NPJ Vascular Health
Citation
Delgado-SanMartin, J.A., Keles, M., Errington, N. et al. Assessing the feasibility of using smartphone data to identify risk of idiopathic pulmonary arterial hypertension. npj Cardiovasc Health 3, 16 (2026). https://doi.org/10.1038/s44325-026-00114-9