Pain-free blood glucose monitoring using wearable sensors: Recent advancements and future prospects

SA Siddiqui, Y Zhang, J Lloret, H Song… - IEEE reviews in …, 2018 - ieeexplore.ieee.org
Keeping track of blood glucose levels non-invasively is now possible due to diverse
breakthroughs in wearable sensors technology coupled with advanced biomedical signal …

De-Hankelization of singular spectrum analysis matrices via an optimization approach for blood glucose estimation

Z Huang, J Gu, WK Ling - 2016 IEEE International Conference …, 2016 - ieeexplore.ieee.org
For the conventional diagonal averaging method, it computes the average of the elements in
each shifted diagonal of each two dimensional singular spectrum analysis matrix to obtain …

Implementable blood glucose estimation with fractional-order system

WX Li, TH Zheng, YW Liu… - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
An implementable blood glucose estimation in computer is presented. In general, the
existing effective approaches for measuring the blood glucose concentration are mainly …

Optimal design of both rectified layer and pooling layer of convolutional neural network for noninvasive blood glucose estimation system

X Wu, Y Liu, J Su, Y Li, WK Ling… - 2016 IEEE 14th …, 2016 - ieeexplore.ieee.org
This paper proposes the optimal designs of both the rectified layer and the pooling layer of
the convolutional neural network for a non-invasive blood glucose estimation system. The …

Extreme Learning Approach for Blood Glucose Estimation

Y Liu, WK Ling, CK Li, S Ho - 2018 11th International …, 2018 - ieeexplore.ieee.org
This paper proposes an extreme learning machine approach for performing the blood
glucose system estimation. The extreme learning machine consists of a unitary matrix in the …