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Proposal of Millimeter-Wave Adaptive Glucose-Concentration Estimation System Using Complex-Valued Neural Networks

This paper proposes an adaptive glucose-concentration estimation system. Diabetes prophylaxis and monitoring require long-term, frequent and accurate observation of blood sugar levels. Electromagnetic measurement is ideal in its non-invasiveness and the possibility of high accuracy. Debye relaxation model indicates that millimeter-wave is promising for this purpose. In this frequency band, however, both phase and magnitude changes have significant meaning. Then, we employ a complex-valued neural network that deals with phase and amplitude information adaptively in a consistent manner. Experiments demonstrate effective estimation of glucose concentration of a realistic range of blood sugar.