Noninvasive Self-monitoring of Blood Glucose at Your Fingertips, Literally!: Smartphone-Based Photoplethysmography

Abstract

Diabetes is a chronic disease and one of the major public health problems worldwide. It is a multifactorial disease, caused by genetic factors and lifestyle habits. Brazil had ∼ 16.8 million individuals living with diabetes in 2019 and is expected to reach 26 million people by 2045. There are global increasing needs for the development of noninvasive diagnostic methods and use of mobile health, mainly in face of the pandemic caused by the coronavirus disease 2019 (COVID-19). For daily glycemic control, diabetic patients use a portable glucometer for glycemic self-monitoring and need to prick their fingertips three or more times a day, generating a huge discomfort throughout their lives. Our goal here is to present a review with very recent emerging studies in the field of noninvasive diagnosis and to emphasize that smartphone-based photoplethysmography (spPPG), powered by artificial intelligence, might be a trend to self-monitor blood glucose levels. In photoplethysmography, a light source travels through the tissue, interacts with the interstitium and with cells and molecules present in the blood. Reflection of light occurs as it passes through the biological tissues and a photodetector can capture these interactions. When using a smartphone, the built-in flashlight is a white light-emitting LED and the camera works as a photodetector. The higher the concentration of circulating glucose, the greater the absorbance and, consequently, the lesser the reflected light intensity will be. Due to these optical phenomena, the signal intensity captured will be inversely proportional to the blood glucose level. Furthermore, we highlight the microvascular changes in the progression of diabetes that can interfere in the signals captured by the photodetector using spPPG, due to the decrease of peripheral blood perfusion, which can be confused with high blood glucose levels. It is necessary to create strategies to filter or reduce the impact of these vascular changes in the blood glucose level analysis. Deep learning strategies can help the machine to solve these challenges, allowing an accurate blood glucose level and interstitial glucose prediction.

Smartphone-Based Screening for Cardiovascular Diseases: A Trend?

“…As the heart contracts, the blood reaches the fingertip, and a video of the fingertip allows recording of the blood perfusion and analysis the color/signal intensity per unit of time (photoplethysmographic waves). 9 When processing the signals obtained by a smartphone or a computer, it is possible to analyze the quantity and morphological characteristics of these pulse waves and to estimate heart rate, oxygen saturation, and blood pressure. 9,11 Figure 1 shows how PPG technology works.…”

“…9 When processing the signals obtained by a smartphone or a computer, it is possible to analyze the quantity and morphological characteristics of these pulse waves and to estimate heart rate, oxygen saturation, and blood pressure. 9,11 Figure 1 shows how PPG technology works. Schoettker et al, 11 compared blood pressure measurements from a smartphone application that analyzes optical PPG signals (OptiBP) with blood pressure measurements by the conventional auscultatory method.…”

Smartphone-based photo analysis for the evaluation of anemia, jaundice and COVID-19

“…1 The use of telemedicine and the development of health applications for smartphones are growing, which allows mobile health (mHealth) to gain global recognition. 2,3 The coronavirus disease 2019 (COVID-19) pandemic offers even further reasons for the development of techniques that do not require interpersonal contact and maintain effective health monitoring. The maintenance of the necessary social distance through the use of healthcare alternatives, such as telemedicine and mHealth applications, leads to the practice of remote monitoring.…”

Remote and non-invasive monitoring of patients with COVID-19 by smartphone

“…The introduction of mobile health and smartphone application for clinical evaluation and monitoring is a new trend and is already part of our daily life (11). Smartphone accessories (flashlight, camera, and microphone), as well as the processing capacity, allow these devices to monitor vital signs and even diseases such as diabetes (12,13) and anemia (14).…”