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An Impedance and Multi-Wavelength Near-Infrared Spectroscopy IC for Non-Invasive Blood Glucose Estimation Kiseok Song , Student Member , IEEE, Unsoo Ha , Student Member , IEEE
提出了一种结合阻抗光谱和多波长近红外光谱的IC,用于高精度无创血糖估计。
0.18 µm CMOS, 38 mW峰值功耗, 12.1 mW最大辐射发射功率
阻抗光谱多波长近红外光谱无创血糖监测人工神经网络频率扫描正弦振荡器
▸结合阻抗光谱(IMPS)和多波长近红外光谱(mNIRS)以提高血糖估计精度
▸采用两步频率扫描正弦振荡器(FSSO)精确测量谐振频率
▸使用人工神经网络(ANN)结合IMPS和mNIRS数据以降低误差
Abstract
A multi-modal spectroscopy IC combining impedance spectroscopy (IMPS) and multi-w avelength near-infrared spec- troscopy (mNIRS) is proposed for high precision non-invasive glucose level estimation. A combination of IMPS and mNIRS can compensate for the glucose estimation error to improve its accuracy. The IMPS circuit measures dielectric characteristics of the tissue using the RLC resonant frequency and the resonant impedance to estimate the glucose level. To accurately fin dr e s - onant frequency, a 2-step freque ncy sweep sinusoidal oscillator (FSSO) is proposed: 1) 8-level coarse frequency switching (f STEP = 9.4 kHz) in 10–76 kHz, and 2) fine analog frequency sweep i nt h e range of 18.9 kHz. During the frequency sweep, the adaptive gain control loop stabilizes the output voltage swing (400 mV p-p). To improve accuracy of mNIRS, three wavelengths, 850 nm , 950 nm, and 1,300 nm, are used. For highly accurate glucose estimation, the measurement data of the IMPS and mNIRS are combined by an artificial neural network (ANN) in external DSP. The proposed ANN method reduces the mean absolute relative difference to 8.3% from 15% of IMPS, and 15–20% of mNIRS in 80–180 mg/dL blood glucose level. The proposed multi-mod al spectroscopy IC occupies 12.5 mm 2 in a 0.18 µm 1P6M CMOS technology and dissipates a peak power of 38 mW with the maximum radiant emitting power of 12.1 mW.