TY - JOUR
T1 - A novel multipurpose device for dataset creation and on-device immediate estimation of blood glucose level from reflection ppg
AU - Mosaddequr, Kazi
AU - Rahman, Tanzilur
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/9
Y1 - 2023/9
N2 - We propose a completely non-invasive and highly accurate portable blood glucose estimator, which is simple hardware that anyone, regardless of their prior experience or knowledge, can use to obtain an immediate reading of their blood sugar level. Glucose levels can be monitored in real time and displayed on the device thanks to its infrared LED light source, sensor with built-in amplification unit, processing unit with blood glucose regression model, power management unit for autonomous operation, and display. The device was initially used to create a dataset of photoplethysmography (PPG) signals collected from the fingertip of 50 subjects. The extracted signal features were correlated with the subject's glucose level, which was measured at the same time using a commercial glucometer, and several regression models were constructed. The models were evaluated using signals from up to 110 subjects across three datasets, and the most optimized model was implemented in the device to predict the subject's blood glucose level solely based on PPG in real-time. The device with the built-in model has been subjected to extensive testing to gauge its efficacy. The device's clinical accuracy is encouraging. The pricey strips and needles that must be purchased along with the hardware in the conventional method will no longer be necessary with this device.
AB - We propose a completely non-invasive and highly accurate portable blood glucose estimator, which is simple hardware that anyone, regardless of their prior experience or knowledge, can use to obtain an immediate reading of their blood sugar level. Glucose levels can be monitored in real time and displayed on the device thanks to its infrared LED light source, sensor with built-in amplification unit, processing unit with blood glucose regression model, power management unit for autonomous operation, and display. The device was initially used to create a dataset of photoplethysmography (PPG) signals collected from the fingertip of 50 subjects. The extracted signal features were correlated with the subject's glucose level, which was measured at the same time using a commercial glucometer, and several regression models were constructed. The models were evaluated using signals from up to 110 subjects across three datasets, and the most optimized model was implemented in the device to predict the subject's blood glucose level solely based on PPG in real-time. The device with the built-in model has been subjected to extensive testing to gauge its efficacy. The device's clinical accuracy is encouraging. The pricey strips and needles that must be purchased along with the hardware in the conventional method will no longer be necessary with this device.
UR - http://www.scopus.com/inward/record.url?scp=85170431311&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2023.e19553
DO - 10.1016/j.heliyon.2023.e19553
M3 - Article
AN - SCOPUS:85170431311
SN - 2405-8440
VL - 9
JO - Heliyon
JF - Heliyon
IS - 9
M1 - e19553
ER -