As one of the necessary diabetes control and treatment methods, the
photoacoustic blood glucose detection technology has great potential due
to its deep detection depth and low interference from stray light.
Previous research mainly focused on improving the detection capabilities
of hardware systems and ignored the exploration of the physical meaning
of the signal itself. We analyzed the characteristics of the signal
amplitude decay in the photoacoustic signal and employed the forced
damping vibration equation to model the signal waveform. A new waveform
feature was constructed to describe the amplitude attenuation rate.
Moreover, facing low accuracy of blood glucose prediction in the case of
small data, we proposed a stable and effective blood glucose detection
combining time-frequency feature and waveform features with evidential
regression. Finally, in human tissue and glucose solution experiments,
the minimum error is achieved 1.02±0.71 mg/dL and 13.28±10.33 mg/dL,