Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML
Crossref DOI link: https://doi.org/10.1038/s41598-024-84265-8
Published Online: 2025-01-02
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Zeynali, Mahdi
Alipour, Khalil
Tarvirdizadeh, Bahram
Ghamari, Mohammad
Text and Data Mining valid from 2025-01-02
Version of Record valid from 2025-01-02
Article History
Received: 13 July 2024
Accepted: 23 December 2024
First Online: 2 January 2025
Declarations
:
: The authors declare no competing interests.