Restoring Severe Quantized Signals for Blood Glucose Estimation

被引:0
|
作者
Liu, Yuwei [1 ,2 ]
Ling, Wing-Kuen [1 ]
Lie, Chi-Kong [2 ]
Ho, Sam [2 ]
机构
[1] Guangdong Univ Technol, Guangzhou Univ Mega Ctr, Sch Informat Engn, 100 Waihuan Xi Rd, Guangzhou 510006, Guangdong, Peoples R China
[2] Shu Tang Informat Technol Shenzhen Co Ltd, Room 1903,Tower 1,Chang Fu Jinmao Bldg,Shihua Rd, Shenzhen, Guangdong, Peoples R China
来源
2020 2ND IEEE INTERNATIONAL WORKSHOP ON SYSTEM BIOLOGY AND BIOMEDICAL SYSTEMS (SBBS) | 2020年
关键词
FILTER;
D O I
10.1109/SBBS50483.2020.9314939
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes an empirical mode decomposition based technique for restoring the severe quantized signals for performing the blood glucose estimation. First, the severe quantized signals are represented by the intrinsic mode functions. Then, the energies of the intrinsic mode functions are computed. The signal is restored by summing up all the intrinsic mode functions with the starting index before the last intrinsic mode function index where the energy of the intrinsic mode function rises. Simulation results show that the proposed method can efficiently restore the severe quantized signals for performing the blood glucose estimation.
引用
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页数:4
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