Authors:
Carlos Hernando Ramiro
;
Manuel Blanco Velasco
;
Eduardo Moreno-Martínez
;
Fernando Cruz Roldán
and
José Sáez Landete
Affiliation:
Departamento de Teoría de la Señal y Comunicaciones, Universidad de Alcalá, Spain
Keyword(s):
ECG compression, Electrocardiogram, Entropy, Maximum compression ratio, Source coding, Thresholding, Wavelet transform.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Wavelet Transform
Abstract:
The aim of electrocardiogram (ECG) compression is to achieve as much compression as possible while the significant information for diagnosis purposes is preserved in the reconstructed signal. The source coding stage allows us to modify the compression ratio without quality degradation through a lossless encoder. In this work, the performance of this stage is analyzed in a compression scheme that has already presented good results among those from the state of the art. The compressor is based on discrete wavelet transform, thresholding and two-role encoder. The study consists of fixing all the stages except the source coding one in order to obtain an upper compression ratio bound. The assessment is based on the entropy of the independent symbols and the minimum expected length of the codewords. The results reveal a gap to improve the compression ratio, so from the previous entropy study an alternative compression method is proposed. For this purpose the symbols probabilities are anal
yzed through the normalized histogram. Thus, a Huffman encoder instead of the two-role one is applied in the new compressor to attain the maximum compression ratio. In this way a significant improvement is obtained without decreasing the original retrieved quality.
(More)