학술논문

A New Method for Dictionary Matrix Optimization in ECG Compressed Sensing
Document Type
Conference
Source
2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Medical Measurements and Applications (MeMeA), 2020 IEEE International Symposium on. :1-6 Jun, 2020
Subject
Engineering Profession
Dictionaries
Electrocardiography
Reconstruction algorithms
Signal reconstruction
Mathematical models
Sensors
Optimization
Compressed Sensing
ECG
Dictionary Optimization
Measurement Quality
Language
Abstract
This paper proposes a new method for dictionary matrix optimization with the aim of improving the reconstruction quality of ECG signals delivered by a Compressed Sensing (CS) algorithm. The method exploits the features common to all the records of the ECG signal of the same patient to obtain an optimized dictionary with reduced size. In this way, the signal reconstruction from the compressed samples is performed in a do-main defined by a base with a reduced cardinality, thus allowing to increase the signal’s reconstruction quality and to reduce the execution time of the reconstruction algorithm. The mathematical model for the patient specific ECG signals dictionary optimization is described, and a preliminary experimental assessment is presented. The obtained results clearly demonstrates that the proposed method exhibits a reconstruction quality in terms of Percentage of Root-mean-squared Difference (PRD) lower than a method adopting the non-optimized dictionary matrix.