Hypomimia, i.e. reduction in the expressiveness of the face, is a cardinal sign of the PD, often present at its early stages. Within the EU-funded i-Prognosis project (http://www.i-prognosis.eu), early and unobtrusive Parkinson’s disease detection tests are developed, based on the interaction of users with everyday technological devices. The selfie analysis module translates facial expression features into an index reflecting the severity of PD hypomimia symptoms that affect the variability of patients’ facial expressions. Monitoring of such an index over time holds the promise to detect the onset of hypomimia symptoms in an unobtrusive way. Our approach proposes a methodology for detecting and quantifying the progressive decrease of variability of facial expressions in early PD patients by analysing patterns emerging from photos (selfies) during daily life. Promising results are presented from both a) a small development set of 36 users (both PD patients and healthy controls) and b) a large set of selfie photos obtained from 1292 users that were analysed by the iPrognosis cloud analysis module.