Remote Photoplethysmography-Based HbA1c Estimation for Community Screening of Type 2 Diabetes Mellitus: Screening Tool or Diagnostic Alternative?

Type 2 diabetes mellitus (T2DM) remains a major global health burden, with a high proportion of undiagnosed cases, particularly in community settings with limited access to laboratory testing. Remote photoplethysmography (rPPG) has emerged as a non-invasive, camera-based technology with potential for scalable screening. This study aimed to evaluate the agreement, diagnostic performance, and clinical role of rPPG-derived HbA1c as a screening tool or diagnostic alternative for T2DM. A cross-sectional diagnostic validation study was conducted among adults in a community setting in Semanan Subdistrict, Jakarta. Participants underwent non-contact facial scanning using an rPPG system alongside standard laboratory measurements of HbA1c and blood glucose. Agreement was assessed using Bland–Altman analysis and Cohen’s Kappa. Diagnostic performance was evaluated using sensitivity, specificity, predictive values, and receiver operating characteristic (ROC) curve analysis. rPPG-derived HbA1c showed a significant mean difference compared with laboratory measurements (0.63%; p < 0.001; 95% CI: 0.34–0.93), indicating systematic bias. Categorical agreement was poor (κ = 0.029; p = 0.403). In screening analysis, sensitivity ranged from 65.38% to 97.37%, while specificity ranged from 8.91% to 59.55%, with consistently high negative predictive values (≥82%). ROC analysis demonstrated an AUC of 0.668 (p = 0.008) for diabetes and 0.711 (p < 0.001) for prediabetes, indicating modest to acceptable discriminative ability. rPPG-based HbA1c estimation lacks sufficient agreement for diagnostic use. However, its relatively high sensitivity and scalability suggest that it may warrant further evaluation as a non-invasive screening tool for early detection and population-level risk stratification within mobile health settings.