Non-invasive glucose prediction system, glucose prediction method, and glucose sensor
AssigneeElectronics and Telecommunications Research Institute
InventorsJoo Yong SIM, Chang-Geun AHN, Bong Kyu KIM, Eun-Ju JEONG, Kwang Hyo CHUNG, Chul HUH
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Abstract
A blood glucose prediction method comprising: acquiring a PAS signal by irradiating light to skin of the body, obtaining a photoacoustic image of the skin from the PAS signal, selecting at least one measurement location based on the photoacoustic image; and predicting the blood glucose based on a photoacoustic spectrum of a PAS signal corresponding to the at least one measurement location among the PAS signals, a blood glucose sensor, and a blood glucose prediction system are provided.
Claims20
A method for predicting blood glucose in a body using a photoacoustic spectrography (PAS), comprising:
- acquiring a PAS signal by irradiating light to skin of the body;
- obtaining a photoacoustic image of the skin from the PAS signal;
- selecting at least one measurement location based on the photoacoustic image;
- and
- predicting the blood glucose based on a photoacoustic spectrum of a PAS signal corresponding to the at least one measurement location among the PAS signals.
A sensor for predicting blood glucose in a body using a photoacoustic spectrography (PAS), comprising:
- a light emitter configured to emit light to skin of the body;
- an acoustic resonator configured to amplifying a PAS signal using at least one cavity, wherein the PAS signal is generated by the skin after absorbing heat of the light;
- and
- a photoacoustic detector configured to acquire the PAS signal amplified by the acoustic resonator.
A system for predicting blood glucose in a body using a photoacoustic spectrography (PAS),
- a blood glucose sensor configured to acquire a plurality of PAS signals corresponding to a plurality of wavelengths by irradiating light having the plurality of wavelengths to the skin;
- and
- a photoacoustic analyzer configured to obtain a plurality of photoacoustic images of skin of the body from the plurality of PAS signals, and predict the blood glucose through machine learning performed based on the plurality of photoacoustic images, wherein the plurality of photoacoustic images corresponds to the plurality of wavelengths of the light, respectively.
Dependencies are inferred from the claim text.