TY - GEN
T1 - Inspection of EEG Signals for Noninvasive Blood Glucose Monitoring in Prediabetes Diagnosis
AU - Igbe, Tobore
AU - Samuel, Oluwarotimi Williams
AU - Li, Jingzhen
AU - Kulwa, Frank
AU - Kandwal, Abhishek
AU - Nie, Zedong
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Prediabetes is a metabolic disorder where the blood glucose (BG) level is higher than normal but not high as diabetes; early diagnosis can prevent health complications and death. However, to determine the BG level, it is required to prick the finger, which causes pain and discomfort. To eliminate this problem, there is a need to investigate noninvasive techniques to estimate BG values and continuous BG monitoring. In this paper, we investigated the changes in electroencephalogram (EEG) frequency parameters that have been scarcely considered for prediabetes diagnosis. We analyzed EEG signals after carrying out an oral glucose tolerance test on 25 participants. Five frequency bands of EEG signals were obtained continuously in 3 positions; frontal (F), occipital (O), and parental (P). The analysis is performed using a boxplot to examine the pattern of the recorded signals. The result shows that the EEG signal from the O position has a sensitivity of 95.3% in the left hemisphere, the P location has 90.3% in the right hemisphere, and F has 93% in the left hemisphere. This observation shows the appropriate location and the combination of EEG frequency parameters, such as the alpha and beta mean power from O and P, which can be integrated into a wearable device to provide a promising clinical solution for noninvasive blood glucose monitoring and prediabetes diagnosis.
AB - Prediabetes is a metabolic disorder where the blood glucose (BG) level is higher than normal but not high as diabetes; early diagnosis can prevent health complications and death. However, to determine the BG level, it is required to prick the finger, which causes pain and discomfort. To eliminate this problem, there is a need to investigate noninvasive techniques to estimate BG values and continuous BG monitoring. In this paper, we investigated the changes in electroencephalogram (EEG) frequency parameters that have been scarcely considered for prediabetes diagnosis. We analyzed EEG signals after carrying out an oral glucose tolerance test on 25 participants. Five frequency bands of EEG signals were obtained continuously in 3 positions; frontal (F), occipital (O), and parental (P). The analysis is performed using a boxplot to examine the pattern of the recorded signals. The result shows that the EEG signal from the O position has a sensitivity of 95.3% in the left hemisphere, the P location has 90.3% in the right hemisphere, and F has 93% in the left hemisphere. This observation shows the appropriate location and the combination of EEG frequency parameters, such as the alpha and beta mean power from O and P, which can be integrated into a wearable device to provide a promising clinical solution for noninvasive blood glucose monitoring and prediabetes diagnosis.
KW - blood glucose
KW - diabetes mellitus
KW - EEG signal
KW - frontal
KW - occipital
KW - OGTT
KW - parental
KW - physiological signal
UR - http://www.scopus.com/inward/record.url?scp=85166381859&partnerID=8YFLogxK
U2 - 10.1109/MeMeA57477.2023.10171941
DO - 10.1109/MeMeA57477.2023.10171941
M3 - Conference Proceeding
AN - SCOPUS:85166381859
T3 - 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Conference Proceedings
BT - 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023
Y2 - 14 June 2023 through 16 June 2023
ER -
