<script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'UA-48293608-1'); </script>
Logo-bi
Bioimpacts. 2025;15: 30589 | Published on: 2025 Aug 09. doi: 10.34172/bi.30589
PMID: 40922953        PMCID: PMC12413980

Original Article

Photoplethysmography based non-invasive blood glucose estimation using systolic-diastolic framing MFCC features and machine learning regression

Ali Kermani 1 * ORCID, Hossein Esmaeili 2

Cited by CrossRef: 0

1- Soliman A, Nor A, Omer O, Mubarak A. A hybrid transfer learning based non-invasive blood glucose monitoring using photoplethysmography signals. Engineering Applications of Artificial Intelligence. 2026;176:114819 [Crossref]
2- Ahuja S, Malhotra S, Yadav J. Real-Time Edge-Deployable Noninvasive Blood Glucose Estimation Using PPG Sensor Signals via a Dual-Stream Spatiotemporal Graph–Transformer. IEEE Sens Lett. 2026;10(5):1 [Crossref]

Poster

As a peer-reviewed international open-access journal, BioImpacts publishes articles on basic and translational aspects of pharmaceutical and biomedical sciences. 
Acceptance rate (2024): 19% 
Publication fee: Free of charge

Indexing/Abstracting Info
PubMed; PubMed Central; Scopus; Science Citation Index Expanded; Google Scholar;   SJR; Essential Science Indicators; Embase; EBSCOhost; CAS: DOAJ: SHERPA/RoMEO
Member of   
Follower of ICMJE
Permission: Creative Commons