A Novel Deep Learning Approach for Non-invasive Blood Glucose Measurement from Photoplethysmography Signals
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-2004-2_34
Reference16 articles.
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3. Monte-Moreno E (2011) Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques. Artif Intell Med 53(2):127–138
4. Habbu S, Dale M, Ghongade R (2019) Estimation of blood glucose by non-invasive method using photoplethysmography. Sadhan ̄ a ̄, 44(6):1–14
5. Salamea C, Narvaez E, Montalvo M (2019) Database proposal for correlation of glucose and photoplethysmography signals. In: The international conference on advances in emerging trends and technologies. Springer, 2019, pp 44–53
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1. Multi-View Cross-Fusion Transformer Based on Kinetic Features for Non-Invasive Blood Glucose Measurement Using PPG Signal;IEEE Journal of Biomedical and Health Informatics;2024-04
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