A Review of Non-Invasive Monitoring of Blood Glucose Levels Based on Photoplethysmography Signals Using Artificial Intelligence

This paper discusses several cutting-edge non-invasive techniques for measuring blood glucose levels (BGL) using photoplethysmography (PPG) signals. These methods can be efficiently and precisely carried out using artificial intelligence algorithms (AI). The most important parameter for identifying the presence of health issues in a person's body is blood glucose. The state of blood circulation is reflected in the PPG signal. PPG-based BGL measurement utilizing AI is a non-invasive measurement approach because BGL measurement is still currently invasive. This study examines the development of this technology using data collected between 2009 and 2022. The future of non-invasive BGL employing PPG signals with artificial intelligence technology looks promising. Further studies may use the findings of the methodological mapping in this review as a guidance when deciding which BGL measuring methodology to use.