This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.

The advancement of age and the increased awareness of public health have resulted in increased demand for continuous vital sign monitoring devices. Therefore, we developed a noninvasive vital sign measurement device without physical resistance to the user using a fiber Bragg grating (FBG) sensor. The FBG sensor was fixed on the wrist, and a pulse wave signal was obtained. Additionally, we focused on the similarity between this pulse wave signal and the second derivative of the plethysmogram (SDPTG). Classifying this signal, we found that its shape changed according to the age and blood pressure. We found that the change in the shape of the pulse wave signal and the SDPTG have the same tendency. Therefore, it is feasible to estimate the vascular age and arteriosclerosis with the signal obtained by an FBG sensor. On the basis of these results, the FBG sensor system can measure multiple vital signs and monitor health more comprehensively.