Improving non-invasive glucose estimation with monthly calibrated photoplethysmography and implicit HbA1c.

ABSTRACT:

Background

Most noninvasive blood glucose technologies, especially wearable photoplethysmography devices, require multiple calibrations and are often limited to narrow cohorts such as unmedicated or mild cases. We assess whether a single pretest once per month can meet clinical accuracy while broadening applicability through cohort-specific models.

Methods

We develop models for three groups: (i) individuals not using antidiabetic drugs, (ii) those using oral antidiabetic drugs only, and (iii) those using antidiabetic drugs in combination with other medications. Models are trained on cohort data with and without the monthly pretest and are then applied directly to personal testing without retraining. Inputs include dual-channel photoplethysmography signals and an inferred HbA

SUBMITTER: Chu J 

PROVIDER: S-EPMC12738703 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature